

                                                         Preliminary Draft

                     Pricing  the  Internet


                                       by


                  Jeffrey  K.  MacKie-Mason

                             Hal  R.  Varian
                         University of Michigan


                                 April 1993
                    Current version: June 14, 1993


Abstract. This is a preliminary version of a paper prepared
for  the  conference  ``Public  Access  to  the  Internet,''  JFK
School  of  Government,  May  26--27  ,  1993.   We  describe
some of the technology and costs relevant to pricing access to
the Internet and suggest a possible smart-market mechanism
for pricing traffic on the Internet.
Keywords.  Networks, Internet, NREN.
Address.  Hal R. Varian, Jeffrey K. MacKie-Mason, Depart-
ment of Economics, University of Michigan, Ann Arbor, MI
48109-1220. E-mail: jmm@umich.edu, halv@umich.edu.

                             Pricing the Internet

                         Jeffrey K. MacKie-Mason
                                 Hal R. Varian

On  December  23,  1992  the  National  Science  Foundation

announced  that  it  will  cease  funding  the  ANS  T3  Internet

backbone in the near future. This is a major step in the tran-

sition from a government-funded to a commercial Internet.

This movement has been welcomed by private providers of

telecommunication  services  and  businesses  seeking  access

to the Internet.

     We think that it is safe to say that no one is quite sure

about how this privatization effort will work.  In particular,

it is far from clear how access to the privatized Internet will

be priced. Currently, the several Internet backbone networks

are public goods with exclusion: usage is essentially free to

all authorized users. Most users are connected to a backbone

through a ``pipe'' for which a fixed access fee is charged,

but the user's organization nearly always covers the access

fee as overhead without any direct charge to the user.1   In

any case, none of the backbones charge for actual usage in

the sense of the volume of data transmitted.

     In this paper we describe some of the technological, cost,

and  economic  issues  related  to  pricing  the  Internet.   We

strongly suspect that efficiency will require usage pricing for
_________________________________________

       We wish to thank Guy Almes,  Eric Aupperle,  Paul Green,  Mark
Knopper,  Ken Latta,  Dave McQueeny,  Jeff Ogden,  Chris Parkin,  Scott
Shenker and Paul Southworth for helpful discussions, advice and data.

  1  Most users of the NSFNET backbone do not pay a pipeline fee to ANS,
the service provider, but instead pay for a connection to their ``regional'' or
mid-level network, which then is granted a connection to the NSFNET.



                                       1

backbone services.  In order to do this, it will be necessary

to  develop  new  standards  for  TCP/IP  packets  in  order  to

facilitate  accounting  and  priority-based  routing.   We  offer

a proposal as to how access might be priced using a smart

market.



1.  Internet Technology and Costs


The Internet is a network of networks. In this paper we focus

on network backbones,  although most of our pricing ideas

apply  equally  well  to  mid-level  and  local  area  networks.

There  are  essentially  three  competing  backbones  for  the

Internet:   ANSnet,  PSInet  and  Alternet.   ANS  is  a  non-

profit  that  was  formed  in  1990  to  manage  the  publicly-

funded NSFNET for research and educational users. ANSnet

now  provides  the  virtual  backbone  service  for  NSFNET,

as well as backbone service for commercial users (through

its  subsidiary,  ANS  CO+RE,  Inc.).   PSInet  and  Alternet

are independent commercial providers of backbone Internet

services to both commercial and non-commercial users.

     The  Internet  is  defined  as  those  connected  networks

that  use  connectionless  packet-switching  communications

technology  based  on  the  TCP/IP  protocols.   Even  though

much of the traffic moves across lines leased from telephone

common carriers, the technology is quite different from the

switched  circuits  used  for  voice  telephony.   A  telephone

user dials a number and various switches then open a line

between the caller and the called number. This circuit stays

open  and  no  other  caller  can  share  the  line  until  the  call

is terminated.  A connectionless packet-switching network,

by contrast, uses statistical multiplexing to maximize use of


                                       2

the communications lines.2   Each circuit is simultaneously

shared by numerous users, and no single open connection is

maintained for a particular communications session:  some

of the data may go by one route while the rest may take a

different route. Because of the technology differences pricing

models appropriate for voice telephony will be inappropriate

for data networks.

     Packet-switching technology has two major components:

packetization  and  dynamic  routing.  A  data  stream  from  a

computer is broken up into small chunks called ``packets.''

The  IP  (Internet  protocol)  specifies  how  to  break  up  a

datastream into packets and reassemble it, and also provides

the  necessary  information  for  various  computers  on  the

Internet (the routers) to move the packet to the next link on

the way to its final destination.

     Packetization  allows  for  the  efficient  use  of  expensive

communications lines. Consider a typical interactive terminal

session to a remote computer.  Most of the time the user is

thinking. The network is needed only after a key is struck or

when a reply is returned. Holding an open connection would

waste most of the capacity of the network link. Instead, the

computer  waits  until  after  a  key  is  struck,  at  which  point

it puts the keystroke information in a packet which is sent

across the network.  The rest of the time the network links

are free to be used for transporting packets from other users.

     With dynamic routing a packet's path across the network

is  determined  anew  for  each  packet  transmitted.   Because

multiple paths exist between most pairs of network nodes,
_________________________________________
  2  ``Connection-oriented'' packet-switching networks also exist:  X.25
and Frame Relay are examples of such.



                                       3

it is quite possible that different packets will take different

paths through the network.3

     The postal service is a good metaphor for the technology

of  the  Internet  (Krol  (1992),  pp.  20--23).   A  sender  puts

a message into an envelope (packet),  and that envelope is

routed through a series of postal stations, each determining

where to send the envelope on its next hop.  No dedicated

pipeline is opened end-to-end, and thus there is no guarantee

that envelopes will arrive in the sequence they were sent, or

follow exactly the same route to get there.

     So that packets can be identified and reassembled in the

correct order, TCP packets consist of a header followed by

data.  The header contains the source and destination ports,

the sequence number of the packet, an acknowledgment flag,

and so on.  The header comprises 20 (or more) bytes of the

packet.

     Once  a  packet  is  built  TCP  sends  it  to  a  router,  a

computer that is in charge of sending packets on to their next

destination.  At this point IP tacks on another header (20 or

more bytes) containing source and destination addresses and

other information needed for routing the packet. The router

then calculates the best next link for the packet to traverse

towards  its  destination,  and  sends  it  on.    The  best  link

may change minute-by-minute, as the network configuration

changes.4  Routes can be recalculated immediately from the
_________________________________________
  3  Dynamic routing contributes to the efficient use of the communications
lines, because routing can be adjusted to balance load across the network.
The other main justification for dynamic routing is network reliability, since
it gives each packet alternative routes to their destination should some links
fail.  This was especially important to the military, which funded most of
the early TCP/IP research to improve the ARPANET.

  4  Routing is based on a dynamic knowledge of which links are up and



                                       4

routing table if a route fails. The routing table in a switch is

updated approximately continuously.

     The data in a packet may be 1500 bytes or so. However,

recently the average packet on NSFNET carries about 200

bytes of data (packet size has been steadily increasing).  On

top of these 200 bytes the TCP/IP headers add about 40; thus

about  17%  of  the  traffic  carried  on  the  Internet  is  simply

header information.

     Over the past 5 years, the speed of the NSFNET backbone

has grown from 56 Kbps to 45 Mbps (``T-3'' service).5 These

lines can move data at a speed of 1,400 pages of text per

second; a 20-volume encyclopedia can be sent across the net

in half a minute. Many of the regional networks still provide

T1 (1.5Mbps) service, but these too, are being upgraded.

     The  transmission  speed  of  the  Internet  is  remarkably

high.  We recently tested the transmission delay at various

times of day and night for sending a packet to Norway. Each

packet traversed 16 links, and thus the IP header had to be

read and modified 16 times, and 16 different routers had to

calculate  the  best  next  link  for  the  transmission.   Despite

the  many  hops  and  substantial  packetization  and  routing

overhead, the longest delay on one representative weekday

was only 0.333 seconds (at 1:10 PM); the shortest delay was

0.174 seconds (at 5:13 PM).

_________________________________________
a static ``cost'' assigned to each link.  Currently routing does not take
congestion into account. Routes can change when hosts are added or deleted
from the network (including failures), which happens often with about 1
million hosts and over 11,000 subnetworks.

  5  In fact, although the communications lines can transport 45 Mbps, the
current network routers can support only 22.5 Mbps service.  ``Kbps'' is
thousand (kilo) bits per second; ``Mbps'' is million (mega) bits per second.



                                       5

Current Backbone Network Costs


The postal service is a good metaphor for packet-switching

technology,  but  a  bad  metaphor  for  the  cost  structure  of

Internet services. Most of the costs of providing the Internet

are  more-or-less  independent  of  the  level  of  usage  of  the

network; i.e., most of the costs are fixed costs. If the network

is  not  saturated  the  incremental  cost  of  sending  additional

packets is essentially zero.

     The NSF currently spends about $11.5 million per year

to operate the NSFNET and provides $7 million per year of

grants to help operate the regional networks.6  There is also

an NSF grant program to help colleges and universities to

connect to the NSFNET. Using the conservative estimate of

1  million  hosts  and  10  million  users,  this  implies  that  the

NSF subsidy of the Internet is less than $20 per year per host,

and less than $2 per year per user.

     Total salaries and wages for NSFNET have increased by

a little more than one-half (about 68% nominal) over 1988-

-1991, during a time when the number of packets delivered

has increased 128 times.7  It is hard to calculate total costs

because  of  large  in-kind  contributions  by  IBM  and  MCI

during the initial years of the NSFNET project, but it appears

that  total  costs  for  the  128-fold  increase  in  packets  have

increased by a factor of about 3.2.

     Two  components  dominate  the  costs  of  providing  a

backbone network: communications lines and routers. Lease
_________________________________________
  6  The regional network providers generally set their charges to recover
the remainder of their costs, but there is also some subsidization from state
governments at the regional level.

  7  Since  packet  size  has  been  slowly  increasing,  the  amount  of  data
transported has increased even more.



                                       6

payments for lines and routers accounted for nearly 80% of


the 1992 NSFNET costs.  The only other significant cost is


for the Network Operations Center (NOC), which accounts


for roughly 7% of total cost.8   In our discussion we focus


only on the costs of lines and routers.
     We have estimated costs for the network backbone as of


1992--93.9  A T-3 (45 Mbps) trunk line running 300 miles


between two metropolitan central stations can be leased for


about  $32,000  per  month.   The  cost  to  purchase  a  router


capable of managing a T-3 line is approximately $100,000.


Assuming another $100,000 for service and operation costs,


and 50-month amortization at a nominal 10% rate yields a


rental cost of about $4900 per month for the router.

_________________________________________
  8  A NOC monitors traffic flow at all nodes in the network and trou-
bleshoots problems.
  9  We estimated costs for the network backbone only, defined to be links
between common carrier Points of Presence (POPs) and the routers that
manage those links.  We did not estimate the costs for the feeder lines to
the mid-level or regional networks where the data packets usually enter and
leave the backbone, nor for the terminal costs of setting up the packets or
tearing them apart at the destination.


                                       7

 Table 1.

 Communications and Router Costs

_(Nominal_$_per_million_bits)1_________________________________________________*
 *_______

__Year________Communications_____________Routers______Design_Throughput________*
 *_______

  1960                         1.00                           2.4 kbps

  1962                                     10.00

  1963                         0.42                          40.8 kbps

  1964                         0.34                          50.0 kbps

  1967                         0.33                          50.0 kbps

  1970                                     0.168

  1971                                     0.102

  1974                         0.11        0.026             56.0 kbps

__1992____________________0.00094_______0.00007_______________45_mbps__________*
 *_______


Notes: 1. Costs are based on sending one million bits of data approximately
1200 miles on a path that traverses five routers.
Sources:  1960--74 from Roberts (1974).  1992 calculated by the authors
using data provided by Merit Network, Inc.


     The costs of both communications and switching have

been dropping rapidly for over three decades. In the 1960s,

digital  computer  switching  was  more  expensive  (on  a  per

packet  basis)  than  communications  (Roberts  (1974)),  but

switching has become substantially cheaper since then.  We

have estimated the 1992 costs for transporting 1 million bits

of data through the NSFNET backbone and compare these

to estimates for earlier years in Table 1.  As can be seen, in

1992 the line cost is about eight times as large as the cost of

routers.

     The topology of the NSFNET backbone directly reflects

the cost structure: lots of cheap routers are used to manage

a limited number of expensive lines. We illustrate a portion

of the network in Figure 1.  Each of the numbered squares

is an RS6000 router; the numbers listed beside a router are


                                       8

links to regional networks. Notice that in general any packet

coming on to the backbone has to move through two separate

routers at the entry and exit node.  For example, a message

we  send  from  the  University  of  Michigan  to  a  scientist  at

Bell Laboratories will traverse link 131 to Cleveland, where

it passes through two routers (41 and 40). The packet goes to

New York, where it again moves through two routers (32 and

33) before leaving the backbone on link 137 to the JVNCnet

regional  network  that  Bell  Labs  is  attached  to.   Two  T-3

communications links are navigated using four routers.



   /afs/umich.edu/user/h/a/halv/Shared/Figures/NetFrag.eps


Figure 1. Network Topology Fragment

Technological and Cost Trends


The decline in both communications link and switching costs

has been exponential at about 30% per year (see the semi-log


                                       9

plot in Figure 2). But more interesting than the rapid decline

in costs is the change from expensive routers to expensive

transmission links. Indeed, it was the crossover around 1970

(Figure 2) that created a role for packet-switching networks.

When  lines  were  cheap  relative  to  switches  it  made  sense

to  have  many  lines  feed  into  relatively  few  switches,  and

to open an end-to-end circuit for each connection.  In that

way, each connection wastes transmission capacity (lines are

held open whether data is flowing or not) but economizes on

switching (one set-up per connection).



 /afs/umich.edu/user/h/a/halv/Shared/Figures/CommCost.eps

Figure  2.   Trends  in  costs  for  communications  links  and

routers.
     When switches became cheaper than lines the network is

more efficient if data streams are broken into small packets

and sent out piecemeal, allowing the packets of many users

to share a single line. Each packet must be examined at each

switch along the way to determine its type and destination,

but this uses the relatively cheap switch capacity.  The gain


                                       10

is that when one source is quiet, packets from other sources

use the same (relatively expensive) lines.

     Although the same reversal in switch and line costs oc-

curred for voice networks, circuit-switching is still the norm

for voice. Voice is not well-suited for packetization because

of variation in delivery delays, packet loss, and packet or-

dering.10   Voice customers will not tolerate these delays in

transmission (although some packetized voice applications

are beginning to emerge as transmission speed and reliability

increases, see (Anonymous (1986)) ).11



2.  Congestion problems


Another  aspect  of  cost  of  the  Internet  is  congestion  cost.

Although congestion costs are not paid for by the providers

of  network  services,  they  are  paid  for  by  the  users  of  the

service.   Time  spent  by  users  waiting  for  a  file  transfer

is  a  social  cost,  and  should  be  recognized  as  such  in  any

economic accounting.

     The  Internet  experienced  severe  congestion  problems

in  1987.    Even  now  congestion  problems  are  relatively

common in parts of the Internet (although not currently on

the T-3 backbone). According to Kahin (1992): ``However,

problems  arise  when  prolonged  or  simultaneous  high-end
_________________________________________
 10  Our tests found packet delays ranging between 156 msec and 425 msec
on a trans-Atlantic route (N=2487 traces, standard deviation = 24.6 msec).
Delays were far more variable to a Nova Scotia site: the standard deviation
was 340.5 msec when the mean delay was only 226.2 msec (N=2467); the
maximum delay was 4878 msec.

 11  The reversal in link and switch costs has had a profound effect on voice
networks. Indeed, Peter Huber has argued that this reversal made inevitable
the breakup of ATT (Huber (1987)). He describes the transformation of the
network from one with long lines all going into a few central offices into
a web of many switches with short lines interconnecting them so that each
call could follow the best path to its destination.



                                       11

uses start degrading service for thousands of ordinary users.

In  fact,  the  growth  of  high-end  use  strains  the  inherent

adaptability of the network as a common channel.''  (page

11.)   It  is  apparent  that  contemplated  uses,  such  as  real-

time video and audio transmission, would lead to substantial

increases in the demand for bandwidth and that congestion

problems  will  only  get  worse  in  the  future  unless  there  is

substantial increase in bandwidth:

          If  a  single  remote  visualization  process  were
     to  produce  100  Mbps  bursts,  it  would  take  only  a
     handful  of  users  on  the  national  network  to  gener-
     ate  over  1Gbps  load.   As  the  remote  visualization
     services move from three dimensions to [animation]
     the  single-user  bursts  will  increase  to  several  hun-
     dred  Mbps  : : :Only  for  periods  of  tens  of  minutes
     to several hours over a 24-hour period are the high-
     end requirements seen on the network.  With these
     applications, however, network load can jump from
     average to peak instantaneously.'' Smarr and Catlett
     (1992), page 167.


There are cases where this has happened. For example dur-

ing  the  weeks  of  November  9  and  16,  1992,  some  packet

audio/visual broadcasts caused severe delay problems, espe-

cially at heavily-used gateways to the NSFNET backbone,

and in several mid-level networks.

     To investigate the nature of congestion on the Internet

we timed the delay in delivering packets to seven different

sites  around  the  world.    We  ran  our  test  hourly  for  37

days  during  February  and  March,  1993.   Deliveries  can

be delayed for a number of reasons other than congestion-

induced  bottlenecks.   For  example,  if  a  router  fails  then

packets  must  be  resent  by  a  different  route.   However,  in

a  multiply-connected  network,  the  speed  of  rerouting  and


                                       12

  delivery of failed packets measures one aspect of congestion,

  or the scarcity of the network's delivery bandwidth.

       Our results are summarized in Figure 3 and Figure 4; we

  present the results only from four of the 24 hourly probes.

  Figure 3 shows the average and maximum delivery delays by

  time of day.  Average delays are not always proportional to

  distance: the delay from Michigan to New York University

  was  generally  longer  than  to  Berkeley,  and  delays  from

  Michigan to Nova Scotia, Canada, were often longer than to

  Oslo, Norway.



/afs/umich.edu/user/h/a/halv/Shared/Figures/DelayAvgMax.eps


  Figure 3.  Maximum and Average Transmission Delays on

  the Internet
                                         13

/afs/umich.edu/user/h/a/halv/Shared/Figures/DelayStdDev.eps


 Figure 4. Variability in Internet Transmission Delays


      There  is  substantial  variability  in  Internet  delays.   For

 example, the maximum and average delays in Figure 3 are

 quite different by time of day.  There appears to be a large

 4PM peak problem on the east coast for packets to New York

 and Nova Scotia, but much less for ATT Bell Labs (in New

 Jersey).12  The time-of-day variation is also evident in Figure

 5, borrowed from Claffy, Polyzos, and Braun (1992).13

      Figure 4 shows the standard deviation of delays by time

 of  day  for  each  destination.    The  delays  to  Canada  are

 extraordinarily variable, yet the delays to Oslo have no more

 variability  than  does  transmission  to  New  Jersey  (ATT).
 _________________________________________
  12  The high maximum delay for the University of Washington at 4PM is
 correct, but appears to be aberrant. The maximum delay was 627 msec; the
 next two highest delays (in a sample of over 2400) were about 250 msecs
 each.  After dropping this extreme outlier, the University of Washington
 looks just like UC Berkeley.

  13  Note that the Claffy et al. data were for the old, congested T-1 network.
 We reproduce their figure to illustrate the time-of-day variation in usage;
 the actual levels of link utilization are generally much lower in the current
 T-3 backbone. Braun and Claffy (1993) show time-of-day variations in T-3
 traffic between the US and three other countries in their Figure 5.



                                        14



 /afs/umich.edu/user/h/a/halv/Shared/Figures/UsageTOD.eps
Figure 5.  Utilization of Most Heavily Used Link in Each

Fifteen Minute Interval (Claffy et al. (1992))


Variability in delay fluctuates widely across times of day, as

we would expect in a system with bursty traffic, but follows

no obvious pattern.

     According  to  Kleinrock  (1992),  ``One  of  the  least  un-

derstood aspects of today's networking technology is that of

network  control,  which  entails  congestion  control,  routing

control, and bandwidth access and allocation.''  We expect

that if access to Internet bandwidth continues to be provided

at  a  zero  cost  there  will  inevitably  be  congestion.   Essen-

tially,  this  is  the  classic  problem  of  the  commons:  unless

the congestion externality is priced, there will inevitably be

inefficient use of the common resource. As long as users face

a zero price for access, they will continue to ``overgraze.''

Hence, it makes sense to consider how networks such as the

Internet should be priced.

     There is a large literature on network congestion control;


                                       15

see Gerla and Kleinrock (1988) for an overview.  However,

there is very little work in using pricing for congestion con-

trol. Cocchi, Estrin, Shenker, and Zhang (1992) and Shenker

(1993) make the important point that if different applications

use different types of network services (responsiveness, re-

liability, throughput, etc.), then it will be necessary to have

some  sort  of  pricing  to  sort  out  users'  demands  for  these

characteristics. These papers lay out the problem in general

and describe how it might be solved.

     Faulhaber (1992) has considered some of the economic

issues related to pricing access to the Internet.  He suggests

that  ``transactions  among  institutions  are  most  efficiently

based on capacity per unit time. We would expect the ANS

to  charge  mid-level  networks  or  institutions  a  monthly  or

annual  fee  that  varied  with  the  size  of  the  electronic  pipe

provided  to  them.   If  the  cost  of  providing  the  pipe  to  an

institution were higher than to a mid-level network : : :the

fee would be higher.''

     Faulhaber's suggestion makes sense for a dedicated line--

-e.g., a line connecting an institution to the Internet backbone.

But  we  don't  think  that  it  is  necessarily  appropriate  for

charging for backbone traffic itself.  The reason is that the

bandwidth on the backbone is inherently a shared resource-

--many packets ``compete'' for the same bandwidth.  There

is an overall constraint on capacity, but there are is no such

thing as individual capacity level on the backbone.14
_________________________________________
 14  Although  it  may  be  true  that  an  institution's  use  of  the  backbo*
 *ne
bandwidth is more-or-less proportional to the bandwidth of its connection
to the backbone.   That is,  the size of an institution's dedicated line to
the backbone may be a good signal of its intended usage of the common
backbone.



                                       16

     Although  we  agree  that  it  is  appropriate  to  charge  a

flat  fee  for  connection  to  the  network,  we  also  think  that

it  is  important  to  charge  on  a  per  packet  basis,  at  least

when the network is congested.  After all,  during times of

congestion the scarce resource is bandwidth for additional

packets.15   The problem with this proposal is the overhead,

or, in economics terms, the transactions cost. If one literally

charged for each individual packet,  it would be extremely

costly  to  maintain  adequate  records.   However,  given  the

astronomical units involved there should be no difficulty in

basing  charges  on  a  statistical  sample  of  the  packets  sent.

Furthermore, accounting can be done in parallel to routing

using much less expensive computers.

     Conversely  when  the  network  is  not  congested  there

is  very  small  marginal  cost  of  sending  additional  packets

through  the  routers.   It  would  therefore  be  appropriate  to

charge users a very small price for packets when the system

is not congested.

     There  has  been  substantial  recent  work  on  designing

mechanisms for usage accounting on the Internet.  The In-

ternet  Accounting  Working  Group  has  published  a  draft

architecture for Internet usage reporting (Internet Account-

ing: Usage Reporting Architecture, July 9, 1992 draft). ANS

has  developed  a  usage  sampling  and  reporting  system  it

calls  COMBits.   COMBits  was  developed  to  address  the

need  to  allocate  costs  between  government-sponsored  re-

search and educational use, and commercial usage, which is
_________________________________________
 15  As we have already pointed out the major bottleneck in backbone
capacity is not the bandwidth of the medium itself, but the switch technology.
We use the term bandwidth to refer to the overall capacity of the network.



                                       17

rapidly growing. COMBits collects an aggregate measure of

packets and bytes usage,  using a statistical sampling tech-

nique.16  However, COMBits only collects data down to the

network-to-network level of source and destination.  Thus,

the resulting data can only be used to charge at the level of the

subnetwork;  the local network administrator is responsible

for splitting up the bill (Ruth and Mills (1992)).17

     Braun and Claffy (1993) describe current traffic patterns

of  the  Internet  by  type  of  application  and  by  international

data flows, and discuss some of the accounting issues that

need to be solved.



Existing support for prioritizing packets


IP  packets  contain  fields  known  Precedence  and  Type  of

Service (TOS). Currently, most commercial routers do not

use  these  fields.18   However,  it  is  widely  anticipated  that

this must change due to increased congestion on the Internet:

``An obvious application would be to allow router and host

configuration to limit traffic entering the internet to be above

some specific precedence. Such a mechanism could be used

to reduce traffic on an internet as often as needed under crisis

conditions'' (Cerf (1993)).

     The  current  interpretations  of  these  fields  described  in

Postel (1981) will probably be changed to the more flexible
_________________________________________
 16  See K. Claffy and Polyzos (1993) for a detailed study of sampling
techniques for measuring network usage.

 17  COMBits has been plagued by problems and resistance and currently
is used by almost none of the mid-level networks.

 18  In 1986 the NSFNET experienced severe congestion and the there was
some experimentation with routing based on the IP precedence field and
the type of application. When the NSFNET was upgraded to T1 capacity,
priority queuing was abandoned for end-user traffic.



                                       18

form  described  in  Almquist  (1992).    Almquist  discusses

only the TOS fields,  and proposes that the user be able to

request that the network should minimize delay, maximize

throughput, maximize reliability, or minimize monetary cost

when delivering the packet. Prototype algorithms to provide

such service are described in Prue and Postel (1988). In this

proposed protocol a router looks up the destination address

and  examines  the  possible  routes.   Each  route  has  a  TOS

number.  If the TOS number of the route matches the TOS

number of the datagram, then that route is chosen. Note that

the TOS numbers must match;  inequality relationships are

not allowed.

     To an economist's eye,  this specification seems some-

what  inflexible.   In  particular,  the  TOS  value  ``minimize

monetary cost'' seems somewhat strange. Of course senders

would want to minimize monetary cost for a given quality

of service:  minimizing monetary cost is an objective, not a

constraint. Also, the fact that TOS numbers do not allow for

inequality relations is strange. Normally, one would think of

specifying the amount that one would be willing to pay for

delivery, with the implicit assumption that any less expensive

service (other things being equal) would be better.

     As Almquist (1992) explains, ``There was considerable

debate over what exactly this value [minimize monetary cost]

should mean.'' However, he goes on to say:

          ``It seems likely that in the future users may need
     some  mechanism  to  express  the  maximum  amount
     they  are  willing  to  pay  to  have  a  packet  delivered.
     However, an IP option would be a more appropriate
     mechanism,  since  there  are  precedents  for  having
     IP  options  that  all  routers  are  required  to  honor,
     and  an  IP  option  could  include  parameters  such  as


                                       19

     the  maximum  amount  the  user  was  willing  to  pay.
     Thus,  the  TOS  value  defined  in  this  memo  merely
     requests that the network ``minimize monetary cost.''
     Almquist (1992)


     Currently there is much discussion in the network com-

munity about what forms of pricing should become part of

the Internet protocol. As Estrin (1989) puts it: ``The Internet

community developed its original protocol suite with only

minimal provision for resource control : : :This time it would

be inexcusable to ignore resource control requirements and

not to pay careful attention to their specification.''



3.  General observations on pricing


The  Internet  uses  scarce  resources.   Telecommunications

lines,  computer  equipment,  and  labor  are  not  free;  if  not

employed by the Internet, they could be put to productive use

in other activities. Bandwidth is also scarce: when the back-

bone is congested, one user's packet crowds out another's,

resulting in dropped or delayed transmissions.  Economics

is concerned with ways to allocate scarce resources among

competing uses, and it is our belief that economics will be

useful in allocating Internet resources as well.

     We are not concerned with pricing the Internet to generate

profits from selling backbone services.  Indeed,  a network

need not be private to be priced; governments are perfectly

capable  of  charging  prices.19    Rather,  our  goal  is  to  find

pricing  mechanisms  that  lead  to  the  most  efficient  use  of

existing resources, and that guide investment decisions in an

appropriate manner.
_________________________________________
 19  In  fact,  many  of  the  mid-level  regional  networks  are  government
agencies, and they charge prices to connect organizations to their networks.



                                       20

     One common resource allocation mechanism is random-

ization: each packet has an equal chance of getting through

(or being dropped). Another allocation scheme is first-come,

first-served: all packets are queued as they arrive and if the

network  is  congested,  every  packet  suffers  a  delay  based

on its arrival time in the queue.  It is easy to see why these

schemes are not good ways to achieve efficiency.20  However

one measures the social value of expeditious delivery for a

packet,  it  will  surely  be  true  that  some  packets  are  worth

more than others.  For example, a real-time video transmis-

sion  of  a  heart  operation  to  a  remote  expert  may  be  more

valuable than a file transfer of a recreational game or picture.

Economic efficiency will be enhanced if the mechanism al-

locating scarce bandwidth gives higher priority to uses that

are more socially valuable.

     We  do  not  want  the  service  provider---government  or

otherwise---to decide which packets are more socially valu-

able and allocate scarce bandwidth accordingly.  We know

from the Soviet experience that allowing bureaucrats to de-

cide whether work shoes or designer jeans are more valuable

is a deeply flawed mechanism.  A price mechanism works

quite differently. The provider knows the costs of providing

services  and  can  announce  these  to  the  users;  users  then

can decide for themselves whether their packets are more or

less valuable than the cost of providing the packet transport

service. When the backbone is congested the cost of service

will be high due to the the cost of crowding out or delaying

the packets of other users; if prices reflect costs only those
_________________________________________
 20  Current backbones use a mix of queuing and random dropping as their
mechanisms for allocating congested capacity.



                                       21

packets with high value will be sent until congestion dimin-

ishes. The users themselves decide how valuable each packet

is, and sort out for themselves which packets are serviced (or

in a multiple service quality network, receive which quality

of service; see Shenker (1993)).

     Furthermore,  if  network  congestion  is  properly  priced,

the revenues collected from the congestion surcharges can

be used to fund further capacity expansion.  Under certain

conditions,  the  fees  collected  from  the  congestion  charges

turn out to be just the ``right'' amount to spend on expanding

capacity. We return to this point below.

     One commonly expressed concern about pricing the In-

ternet is that ``poor'' users will be deprived of access.  This

is not a problem with pricing,  but with the distribution of

wealth.   A  pricing  mechanism  determines  how  the  scarce

bandwidth  will  be  allocated  given  the  preferences  and  re-

sources of the users.  If we wish to ensure that certain users

have sufficient resources to purchase a base level of services

then we can redistribute initial resources, say by providing

vouchers or lump sum grants.21

     Universal access and a base endowment of usage for all

citizens---if desired---can be provided through vouchers or

other  redistribution  schemes.   But  for  a  given  distribution

of  resources,  how  should  backbone  services  be  allocated?

They are currently allocated (among paid-up subscribers) on
_________________________________________
 21  Food stamps are an example of such a scheme. The federal government
more or less ensures that everyone has sufficient resources to purchase a
certain amount of food. But food is priced, so that given one's wealth plus
food stamps, the consumer still must decide how to allocate scarce resources
relative to the costliness of providing those resources. The government does
not guarantee unlimited access to foodstuffs, nor to all varieties of caloric
substances (alcoholic beverages are not eligible).



                                       22

the basis of randomization and first-come,  first-served.  In

other words, users are already paying the costs of congestion

through delays and lost packets.  A pricing mechanism will

convert delay and queuing costs into dollar costs.  If prices

are designed to reflect the costs of providing the services,

they will force the user to compare the value of her packets

to the costs she is imposing on the system.  Allocation will

then be on the basis of the value of the packets, and the total

value of service provided by the backbones will be greater

than under a non-price allocation scheme.

     In  the  rest  of  the  paper  we  discuss  how  one  might

implement pricing that reflects the cost (including congestion

costs)  of  providing  backbone  services.   We  begin  with  a

review of some current pricing schemes and their relationship

to costs.



4.  Current Pricing Mechanisms


NSFNET,  the  primary  backbone  network  of  the  Internet,

has been paid for by the NSF, IBM, MCI and the State of

Michigan until the present.22  However, most organizations

do not connect directly to the NSFNET. A typical university

will  connect  to  its  regional  mid-level  network;  the  mid-

level maintains a connection to the NSFNET. The mid-level

networks (and a few alternative backbone networks) charge

their customers for access.

     There  are  dozens  of  companies  that  offer  connections

to the Internet.  Most large organizations obtain direct con-

nections,  which  use  a  leased  line  that  permits  unlimited
_________________________________________
 22  NSF restricts the use of the backbone to traffic with a research or
educational purpose, as defined in the Acceptable Use Policies.



                                       23

usage subject to the bandwidth of the line. Some customers


purchase ``dial-up'' service which provides an intermittent


connection, usually at much lower speeds.  We will discuss


only direct connections below.

     Table 3 summarizes the prices offered to large universi-


ties by ten of the major providers for T-1 access (1.5 mbps).23


There are three major components: an annual access fee, an


initial connection fee and in some cases a separate charge


for the customer premises equipment (a router to serve as


a  gateway  between  the  customer  network  and  the  Internet


provider's network).24  The current annualized total cost per


T-1 connection is about $30--35,000.


_________________________________________
 23  The  fees  for  some  providers  are  dramatically  lower  due  to  public
subsidies.

 24  Customers will generally also have to pay a monthly ``local loop''
charge to a telephone company for the line between the customer's site and
the Internet provider's ``point of presence'' (POP), but this charge depends
on mileage and will generally be set by the telephone company, not the
Internet provider.



                                       24




     All of the providers use the same type of pricing: annual

fee  for  unlimited  access,  based  on  the  bandwidth  of  the

connection.   This  is  the  type  of  pricing  recommended  by

Faulhaber (1992).  However, these pricing schemes provide

no incentives to flatten peak demands, nor any mechanism for

allocating network bandwidth during periods of congestion.

It  would  be  relatively  simple  for  a  provider  to  monitor  a

customer's usage and bill by the packet or byte. Monitoring

requires only that the outgoing packets be counted at a single

point: the customer's gateway router.

     However,  pricing  by  the  packet  would  not  necessarily

increase the efficiency of network service provision, because

the  marginal  cost  of  a  packet  is  nearly  zero.  As  we  have

shown, the important scarce resource is bandwidth, and thus


                                       25

efficient prices need to reflect the current state of the network.

Neither a flat price per packet nor even time-of-day prices

would come very close to efficient pricing.
5.  Matching prices to costs



In general we want the prices that users face to reflect the

resource  costs  that  they  generate  so  that  they  can  make

intelligent decisions about resource utilization. In the case of

the Internet, there are several costs that might be considered:



  o  The fixed costs of providing the network infrastruc-

     ture.  As we have seen this is basically the rent for the

     line, the cost of the routers, and the salary for the support

     staff.


  o  The  incremental  costs  of  sending  extra  packets.   If

     the network is not congested, this is essentially zero.


  o  The social costs of delaying other users' packets when

     the network is congested. This is not directly a resource

     cost, but should certainly be considered part of the social

     cost of a packet.


  o  The cost of expanding capacity of the network. This

     will normally consist of adding new routers, new lines,

     and new staff.


     We  first  consider  how  ideal  prices  would  incorporate

this cost information, then consider how market-based prices

might work.
                                       26

The incremental costs of sending extra packets.


The price of sending a packet in a non-congested network

should be close to zero; any higher price is socially inefficient

since  it  does  not  reflect  the  true  incremental  costs.    If

the  incremental  cost  is  high  enough  to  justify  the  cost  of

monitoring and billing, it should be charged as a per-packet

cost.25
The social costs of delaying other users' packets when the

network is congested.


The  price  for  sending  a  packet  when  the  network  is  in  a

congested state should be positive:  if my packet precludes

(or delays) another user's packet, then I should face the cost

that I impose on the other user. If my packet is more valuable

than hers, then it should be sent; if hers is more valuable than

mine, then hers should be sent.

     We  can  depict  the  logic  of  this  argument  graphically

using demand and supply curves.  Suppose the packet price

were very high;  then only a few users would want to send

packets.  As the packet price decreases,  more users would

be willing to send more packets. We depict this relationship

between price and the demand for network access in Figure

6. If the network capacity is some fixed amount K, then the

optimal price for access is where the demand curve crosses

the capacity supply. If demand is small relative to capacity,

the efficient price is zero---all users are admitted. If demand

_________________________________________
 25  Note  that  much  of  the  necessary  monitoring  and  billing  cost  may
already be incurred to implement our other pricing proposals.
                                       27



   /afs/umich.edu/user/h/a/halv/Shared/Figures/Demand.eps



Figure 6.  Demand for network access with fixed capacity.

When demand is low, the packet price is low. When demand

is high, the packet price is high.


is high, users that are willing to pay more than the price of

admission to the network are admitted; the others are not.

     This analysis applies for the extreme case where there is

a fixed capacity.  If increase in use by some agents imposes

delay on other agents, but not outright exclusion, the analysis

is slightly different.  Suppose that we know the amount of

delay as a function of number of packets, and that we have

some idea of the costs imposed on users by a given amount of

delay. Then we can calculate a relationship between number

of packets sent and delay costs. The relevant magnitude for

determining the optimal number of users is the marginal cost

of delay, as depicted in Figure 7.

     The efficient price is where the marginal willingness to

pay for an additional packet just covers the marginal increase

in delay costs generated by that packet.  If a potential user

faces this price he will be able to compare his own benefit

from sending a packet to the marginal delay costs that this

imposes on other users.



                                       28



/afs/umich.edu/user/h/a/halv/Shared/Figures/DemandSupply.eps



  Figure 7.  Demand for network access with a marginal cost

  of delay. When demand is low, the packet price is low. When

  demand is high, and congestion is high, the packet price is

  high.


  The cost of expanding capacity of the network.


  If the network usage never reaches capacity, even at a zero

  price of packets, then clearly there is no need for expanding

  capacity. It is only appropriate to expand capacity when the

  network is sometimes congested.  Consider first the model

  with fixed capacity. If the packet prices are set correctly, we

  have seen that they measure the marginal value of the last

  admitted packet.  If the cost of expanding capacity enough

  to accommodate one more packet is less than the marginal

  value of that packet, then it makes economic sense to expand

  capacity.   If  this  condition  is  not  satisfied,  then  capacity

  expansion is not economically worthwhile.


       Hence the optimal congestion prices play a two roles---

  they serve to efficiently ration access to the network in times

  of congestion and they send the correct signals with respect

  to capacity expansion.  In this framework, all the revenues


                                         29

generated by congestion prices should be plowed back into

capacity expansion.

     Note  that  only  the  users  who  want  to  use  the  network

when  it  is  at  capacity  pay  for  capacity  expansion.   Users

who  are  willing  to  wait  until  after  the  demand  peak  do

not pay anything towards expanding network capacity.  We

think that this point is important from a political perspective.

The largest constituency of the Internet apparently is e-mail

users.26  A proposal to charge high prices for e-mail is likely

to  be  politically  infeasible.   However,  e-mail  can  usually

tolerate moderate delays.  Under congestion pricing of the

sort we are describing, e-mail users could put a low or zero

bid price on their traffic, and would continue to face a very

low cost.

     The situation is only slightly different in the case of delay

costs.  Here the price measures the marginal benefit of an

additional  packet  (which  is  equal  to  the  marginal  cost  of

delay); if additional investment can reduce the marginal cost

of  delay  by  more  than  the  willingness-to-pay  for  reduced

delay then it should be undertaken, otherwise it should not.

We examine the analytics of pricing a congested network in

the Appendix 1.  It turns out that essentially the same result

holds: if the packet price is chosen to be optimal with respect

to delay and congestion costs it will be the appropriate price

to use for determining whether capacity should be expanded.

_________________________________________
 26  More traffic is generated by file transfers, but this reflects fewer users
sending bigger data streams (files vs. e-mail messages).
                                       30

The fixed costs of providing the network infrastructure.


Think  of  the  initial  investment  in  network  infrastructure

as  a  discrete  decision:   if  you  pay  a  certain  amount  of

money  you  can  create  a  usable  network  of  minimal  size.

Further expansion can be guided by the congestion prices,

as indicated above. But what criterion can be used to decide

whether the initial investment is warranted?

     The  simple  answer  is  that  the  investment  should  be

undertaken  if  total  benefits  exceed  costs.   But  since  the

existence  of  the  network  is  a  public  good  that  provides

benefits for all users, we have to add up all potential users'

willingnesses-to-pay for the network infrastructure, and see

if this total willingness-to-pay exceeds the cost of provision.

     In the case of a computer network like the Internet, it is

natural to think of paying for the network infrastructure via

a flat access fee.  Each party who connects to the network

pays a flat price for network access distinct from the usage

based fee described earlier.  In general,  these connect fees

will be different for different people, since different people

and institutions will value connection to the net differently.

Note that in general efficiency will require some sort of price

discrimination in connect fees;  but it will also require that

users pay the same prices for congestion fees.


     In  summary:  there  are  four  types  of  costs  associated

with providing a broad-based computer network: 1) the fixed

costs of providing initial infrastructure; 2) the marginal costs

of sending packets when the network is not congested;  3)

the congestion costs of sending packets when the network is

congested; 4) the costs of expanding capacity.  An efficient

pricing mechanism will have a structure that is parallel to


                                       31

this cost structure: 1) a fixed connection charge that differs

from  institution  to  institution;  2)  a  packet  charge  close  to

zero when the network is not congested; 3) a positive packet

charge when the network is congested; 4) the packet charge

revenues  can  then  be  used  to  guide  capacity  expansion

decisions.



6.  Implementing prices


We  have  argued  that  prices  should  reflect  costs.   But  we

have not yet considered how these efficient prices should be

implemented. We turn now to that task.

     The connect charges are the easiest to deal with,  since

that is very much like the current methods of charging for

provision. Each customer pays a flat fee for connection; often

this fee will depend on the characteristics of the customer

(educational, commercial) and on the size of the bandwidth of

the connection. Presumably the bandwidth of the connection

purchased by a user is correlated to some degree with the

user's willingness to pay, so this should serve as a reasonable

characteristic upon which to base connect charges.27

     A zero cost of packet charges when the network is not

congested is not hard to arrange either---that's what we have

now.  The novel part of the pricing mechanism we propose

is  the  per  packet  congestion  charge.   We  have  discussed

how one might implement such a fee in MacKie-Mason and

Varian  (1993).   We  briefly  review  that  proposal  here.   In

Appendix 2 we describe some of the details that would be

necessary to implement a smart market.
_________________________________________
 27  We intend to investigate how a profit-maximizing or welfare-maximizing
provider of network access might price discriminate in connect fees in future
work.



                                       32

     If congestion has a regular pattern with respect to time of

day, or day of week, then prices could vary in a predictable

way over time. However, this is a relatively inflexible form

for pricing. We think that it would be better to use a ``smart

market'':  a  price  for  packet  access  to  the  net  that  varies

minute-by-minute to reflect the current state of the network

congestion.

     This  would  not  be  terribly  difficult  to  implement,  at

least in a minimal form.  Each packet would have a ``bid''

field in the header that would indicate the willingness-to-pay

for that packet.  Users would typically set default bids for

various applications, then override these defaults in special

circumstances.  For example, a user might assign a low bid

to e-mail packets, for which immediate access to the net is

usually not required. Real-time audio or visual data might be

assigned a high bid price. The network would then admit all

packets whose bid exceeded some cutoff amount. The cutoff

amount  is  determined  by  the  condition  that  the  marginal

willingness-to-pay for an additional packet has to equal the

marginal congestion costs imposed by that packet.

     A  novel  feature  of  this  kind  of  smart  market  is  that

users do not pay the price that they actually bid; rather they

pay  for  their  packets  at  the  market-clearing  price,  which

by construction will be lower than the bids of all admitted

packets.   Note  how  this  is  different  from  priority-pricing

by  say,  the  post  office.  In  the  post-office  model  you  pay

for first-class mail even if there is enough excess capacity

that  second-class  mail  could  move  at  the  same  speed.   In

the smart market described here,  a user pays at most their

willingness-to-pay for an additional packet.


                                       33

     The smart market has many desirable features.  By con-

struction  the  outcome  is  the  classic  supply-equals-demand

level  of  service  of  which  economists  are  so  fond.28    The

equilibrium  price,  at  any  point  in  time,  is  the  bid  of  the

marginal user. Each infra-marginal user is charged this price,

so each infra-marginal user gets positive consumer surplus

from his or her purchase.

     The  major  differences  from  the  textbook  demand  and

supply  story  is  that  no  iteration  is  needed  to  determine

the  market-clearing  price---the  market  is  cleared  as  soon

as  the  users  have  submitted  their  bids  for  access.29    This

mechanism can be viewed as a Vickrey auction where the n

highest bidders gain access at the n + 1st highest price bid.30
     We  have  assumed  that  the  bid-price  set  by  the  users

accurately  reflects  the  true  willingness-to-pay.  One  might

well ask whether users have the correct incentives to reveal

this value: is there anything to be gained by trying to ``fool''

the smart market?  It turns out that the answer is ``no.''  It

can be shown that it is a dominant strategy in the Vickrey

auction to bid your true value, so users have no incentive to

misprepresent their bids for network access. By the nature of
_________________________________________
 28  For good reason, we might add.


 29  Of course,  in real time operation,  one would presumably cumulate
demand over some time interval.   It is an interesting research issue to
consider how often the market price should be adjusted. The bursty nature
of Internet activity suggests a fairly short time interval. However, if users
were charged for the congestion cost of their usage, it is possible that the
bursts would be dampened.

 30  Waldspurger,  Hogg,  Huberman,  Kephart,  and Stornetta (1992) de-
scribes some (generally positive) experiences in using this kind of ``second-
bid'' auction to allocate network resources. However, they do not examine
network access itself, as we are proposing here.



                                       34

the auction, you are assured that you will never be charged

more  than  this  amount  and  normally  you  will  be  charged

much less.



7.  Remarks about the smart market solution
Who sets the bids?


We expect that choice of bids would be done by three parties:

the local administrator who controls access to the net,  the

user  of  the  computer,  and  the  computer  software  itself.

An organization with limited resources, for example, might

choose  low  bid  prices  for  all  sorts  of  access.  This  would

mean that they may not have access during peak times, but

still would have access during off-peak periods.31

     Within  any  limits  imposed  by  institution  policies,  the

users  could  then  set  priority  values  for  their  own  usage.

Normally,  users would set default values in their software

for  different  services.   For  example,  file  transfers  might

have lower priority than e-mail, e-mail would be lower than

telnet (terminal sessions), telnet would be lower than audio,

and so on.  The user could override these default values to

express his own preferences---if he was willing to pay for

the increased congestion during peak periods.

     Note that this access control mechanism only guarantees

relative  priority,  not  absolute  priority.   A  packet  with  a
_________________________________________
 31  With bursty traffic, low-priority packets at ``peak time'' might experi-
ence only moderate delays before getting through. This is likely to be quite
different from the telephone analogue of making customers wait until after
10PM to obtain low-priority, low-rate service. The average length of delays
for low-priority traffic will depend on the average level of excess capacity
in the system. One advantage of our scheme is that it correctly signals the
efficient level of capacity to maintain.



                                       35

high bid is guaranteed access sooner than a low bid, but no

absolute guarantees of delivery time can be made.32  Rejected

packets could be bounced back to the users, or be routed to

a slower network, possibly after being stored for a period in

a buffer in case the permitted priority level falls sufficiently

a short time later.



Offline accounting


If the smart market system is used with the sampling system

suggested  earlier  the  accounting  overhead  doesn't  have  to

slow things down much since it can be done in parallel. All

the router has to do is to compare the bid of a packet with the

current value of the cutoff.  The accounting information on

every 1000th  packet, say, is sent to a dedicated accounting

machine  that  determines  the  equilibrium  access  price  and

records  the  usage  for  later  billing.33   However,  such  sam-

pling  would  require  changes  in  current  router  technology.

Such accounting may well prove expensive.  NSFNET has

modified routers to collect sampled usage data; they found

that the cost of the monitoring system is significant.



Network stability


Adding  bidding  for  priority  to  the  routing  system  should

help  maintain  network  stability,  since  the  highest  priority

packets  should  presumably  be  the  packets  sent  between
_________________________________________
 32  It is hard to see how absolute guarantees can be made on a connec-
tionless network.  However, there have been proposals to provide hybrid
networks, with some connection-oriented services in parallel to the connec-
tionless services. Connection-oriented services are well-suited for delivery
guarantees.

 33  We don't discuss the mechanics of the billing system here. Obviously,
there is a need for COD, third-party pricing, and other similar services.



                                       36

routers that indicate the state of the network. These network

``traffic cops'' could displace ordinary packets so as to get

information through the system as quickly as possible.

     In fact, administrative information currently moves though

the  network  at  a  higher  priority  than  regular  traffic.   This

allows the administrators to update routing tables, etc.  in a

more timely manner. The fact that such prioritized routing is

already in place, albeit in a limited form, indicates that it is

at least feasible to consider extending the prioritization to a

broader set of users.


Fluctuations in the spot market price


Many readers have been unhappy with the idea that the price

of bandwidth would fluctuate in the smart market system. It

is felt by some that having predictable prices and budgets is

important to users. We have several responses to this set of

issues. First, everything depends on how much expenditures

fluctuate.   If  prices  and  uses  of  the  network  turn  out  to

be relatively predictable, expenditures would fluctuate very

little.   Enterprises  have  little  difficulty  now  dealing  with

fluctuations in postage, electricity, and telephone bills from

month to month, and there is no reason to expect that network

usage would be different.

     Second,  it  is  important  to  remember  that  in  the  smart

market, prices only fluctuation down. The user (or the user's

application) sets the maximum he or she is willing to pay for

network access; the actual price paid will almost always be

less than this.  Furthermore,  the user should have virtually

instantaneous feedback about the current state of his or her

expenditures, so there should be little difficulty in budgetary

control.


                                       37

     Finally, the most important point that we need to make

is that the price set by the smart market is a ``wholesale''

price,  not necessarily a ``retail'' price.  If a particular user

doesn't want to bear the risk of price fluctuations, he or she

can always contract with another party who is willing to bear

that  risk.   This  party  may  be  the  supplier  of  the  network

service, or it may be a third party.

     For example, consider an extreme case where the network

price  has  significant  fluctuations:  the  price  for  an  hour  of

teleconferencing at a particular time of day could be $200

or could be $50. A third party could offer to sell bandwidth

to anyone demanding it at, say, $100 an hour.  If the price

turned out to be $50, the bandwidth reseller would make a

profit;  if  it  turned  out  to  be  $200,  the  bandwidth  reseller

would make a loss. But the purchaser would pay a flat $100

no matter what.

     If the price fluctuations are large, it may well happen that

most retail customers buy bandwidth on a contract basis at a

fixed price.  But the fact that the spot market is available is

very important since it allows ``wholesale'' customers to buy

bandwidth on an ``as available'' basis, thereby encouraging

efficient use of bandwidth.


Short term price fluctuations


Another problem arises at the other end of the time scale. It is

widely observed that packet transfers are ``bursty.'' Traffic

on  the  network  fluctuations  quite  significantly  over  short

time periods.  Can a market price keep up with this kind of

fluctuation?

     We have two answers to this question.  First, it is very

easy  to  buffer  packets  for  short  time  intervals.   When  a


                                       38

high-priority/high-bid burst comes along, packets with low

priority  and  low  bid,  are  buffered.  After  the  high-priority

packets are admitted, the low-priority packets move onto the

network.  In network engineering this is known as priority-

based routing, and is a reasonably well-understood policy.

     The second answer is a bit deeper. We conjecture that if

usage were priced in the way we advocate, network traffic

would  be  a  lot  less  bursty.   Said  another  way:  bursts  in

network traffic are there now because there is no charge for

bursts. If bursts were costly to the user there would be fewer

of them.

     Of course, this is not only because the user would change

behavior---the  bursts  are  at  a  much  higher  frequency  than

the users control. Rather, the users would have an incentive

to use applications that smoothed the network traffic flow.

In countries where electricity is priced by time of day, water

heaters are smart enough to heat water in the middle of the

night when rates are low. If a refrigerator can be that smart,

think  what  a  workstation  could  do---if  it  know  the  right

prices.



Routing


As we have mentioned several times, the Internet is a connec-

tionless network. Each router knows the final destination of a

packet, and determines, from its routing tables, what the best

way is to get from the current location to the next location.

These routing tables are updated continuously to indicate the

current state of the network. Routing tables change to reflect

failed links and new nodes, but they do not change to reflect

congestion  on  various  links  of  the  network.  Indeed,  there


                                       39

is no standard measurement for congestion available on the

current NSFNET T-3 network.

     Currently, there is no prioritization of packets: all packets

follow the same route at a given time. However, if each packet

carried a bid price, as we have suggested, this information

could be used to facilitate routing through the Internet.  For

example, packets with higher bids could take faster routes,

while packets with lower bids could be routed through slower

links.

     The  routers  could  assign  access  prices  to  each  link  in

the net, so that only packets that were ``willing to pay'' for

access to that link would be given access.  Obviously this

description is very incomplete, but it seems likely that having

packets bid for access will help to distribute packets through

the network in a more efficient way.


Distributional aspects


As we mentioned earlier, the issue of pricing the Internet is

highly politicized. One nice feature of smart market pricing is

that low-priority access to the Internet (such as e-mail) would

continue  to  have  a  very  low  cost.   Indeed,  with  relatively

minor public subsidies to cover the marginal resource costs,

it would be possible to have efficient pricing with a price of

close to zero most of the time, since the network is usually

not congested.

     If there are several competing carriers, the usual logic of

competitive bidding suggests that the price for low-priority

packets should approach marginal cost---which, as we have

argued, is essentially zero. In the plan that we have outlined

the high priority users would end up paying most of the costs

of the Internet.


                                       40

Price uncertainty


Several readers have objected to the use of the smart market

since it adds an element of price uncertainty: the user won't

necessarily know the price for access to the network unless

he inquires beforehand.  We don't think that this would be

a big problem for several reasons.  First,  it is important to

remember  that  the  user  (or  the  application)  has  complete

control  over  the  maximum  price  that  he  or  she  is  willing

to pay.  Second, we imagine that there would be reasonably

predictable  patterns  in  usage  so  that  users  would  have  a

good  idea  when  congestion  is  likely  to  occur.   Third,  if

there is some uncertainty about the current price,  the user

could simply query the router.  Finally, we think that if the

congestion  prices  are  used  to  guide  investment  decisions,

the demand of the users and the supply of network capacity

should  be  closely  enough  matched  so  that  the  congestion

prices would normally be rather small.

     It is also worthwhile to note that the fluctuations in price

represent a real resource cost---congestion costs. If the user

doesn't bear that cost, then someone else will have to:  the

other users who find their packets delayed or dropped.  Of

course, there is no reason why the risk of price fluctuations

couldn't  be  borne  by  third-parties.   One  could  imagine  a

futures market for bandwidth in which third-parties offer to

absorb the risk of price fluctuations for a fee.



Interruptible service


Implementing the smart market mechanism for pricing con-

gestion on the Internet would involve adding new information

to the TCP/IP headers. It will take a considerable amount of


                                       41

discussion and debate to accomplish this. However, there is

a partial way to handle congestion pricing that requires very

little change in existing protocols.

     Suppose  that  providers  of  Internet  services  had  two

classes  of  service:   full  service  and  interruptible  service.

Users would pay a flat fee based on the size of their pipeline

for the type of service they preferred and full service would

cost more than interruptible service.

     When the load on the routers used by the Internet provider

reached a certain level, the users who had purchased inter-

ruptible service would be denied access until the congestion

subsided.   All  that  is  needed  to  implement  this  rationing

mechanism is a simple change to the routing algorithms.

     The  defect  of  interruptible  service  is  that  it  is  rather

inflexible compared to the smart market solution: it applies

to all participants in a single administrative billing unit and

cannot be overridden by individual users. On the other hand

it  is  very  simple  to  implement.   See  Wilson  (1989)  for  a

detailed study of the analytics of interruptible service.



8.  Role of public and private sector


As  we  have  seen,  current  private  providers  of  access  to

the  Internet  generally  charge  for  the  ``size  of  the  pipe''

connecting users to the net.  This sort of pricing is probably

not too bad from an efficiency point of view since the ``size

of  the  pipe''  is  more-or-less  proportional  to  contemplated

peak usage.

     The  problem  is  that  there  is  no  pricing  for  access  to

the common backbone.  In December of 1992, the NSF an-

nounced that it would stop providing direct operation funding


                                       42

for the ANS T-3 Internet backbone. It is not yet clear when

this  will  actually  happen,  although  the  cooperative  agree-

ment  between  NSF  and  Merit  has  been  extended  through

April 1994. According to the solicitation for new proposals,

the NSF intends to create a new very high speed network

to  connect  the  supercomputer  centers  which  would  not  be

used for general purpose traffic. In addition, the NSF would

provide funding to regional networks that they could use to

pay for access to backbone networks like ANSnet,  PSInet

and Alternet.

     The  NSF  plan  is  moving  the  Internet  away  from  the

``Interstate''  model,  and  towards  the  ``turnpike''  model.

The ``Interstate'' approach is for the government to develop

the ``electronic superhighways of the future'' as part of an

investment in infrastructure. The ``turnpike'' approach is that

the private sector should develop the network infrastructure

for Internet-like operations, with the government providing

subsidies to offset the cost of access to the private networks.

     Both funding models have their advantages and disad-

vantages.   But  we  think  that  an  intermediate  solution  is

necessary.  The private sector is probably more flexible and

responsive  than  a  government  bureaucracy.  However,  the

danger is that competing network standards would lead to an

electronic Tower of Babel. It is important to remember that

turnpikes have the same traffic regulations as the Interstates:

there  is  likely  a  role  for  the  government  in  coordinating

standards setting for network traffic. In particular, we think

that  it  makes  sense  for  the  government,  or  some  industry

consortium, to develop a coherent plan for pricing Internet

traffic at a packet level.34
_________________________________________
 34  One of the recent bills submitted by Representative Boucher to begin



                                       43

     It is worth remarking on the history of standards for voice

networks. U.S. voice communications are now provided by

a mesh of overlapping and connected networks operated by

multiple, competing providers (ATT, MCI and Sprint being

the largest). This is quite a bit like the situation we expect to

emerge for data networks. However, over the decades when

switching  and  billing  standards  were  being  designed  and

refined, the only significant provider was ATT, so it could

impose  a  single,  coordinated  standard  that  later  providers

accepted.   International  voice  networks,  by  contrast,  have

always required interconnection and traffic handoff between

various (mostly national) providers. Standards were designed

and imposed by a public body, the CCITT.

     A pricing standard has to be carefully designed to contain

enough  information  to  encourage  efficient  use  of  network

bandwidth,  as  well  as  containing  the  necessary  hooks  for

accounting and rebilling information.  A privatized network

is simply not viable without such standards, and work should

start immediately on developing them.


_________________________________________
implementing the NREN requires uniform protocols for interconnection
between providers. It is not clear whether the bill will also mandate uniform
standards for providing management information like accounting data.



                                       44

Appendix  1:   Some  analytics  of  pricing  a  congestible

resource


     The  classic  ``problem  of  the  commons''  describes  a

situation where property that is held in common will tend

to be overexploited.  Each user is aware of his private costs

incurred by accessing the common property but neglects the

costs he imposes on others. In the context of the Internet we

have seen that the scarce resource is the switching capacity

of  the  routers.  When  the  network  is  highly  congested,  an

additional  user  imposes  costs  on  other  users  to  the  extent

that his use of switching capacity prevents, or at least slows

down, the use of the same capacity by other users.

     Efficient use of the switch capacity requires that users

that are willing to pay more for access should be admitted

before  users  with  lower  willingness-to-pay.  The  price  for

admission to the switches should be that price that reflects

the social cost of an additional packet.

     Here  we  briefly  examine  some  of  the  analytics  of  a

standard  (static)  congestion  model.35    Arnott,  de  Palma,

and  Lindsey  (1990)  have  argued  strongly  that  congestion

models should examine dynamic microbehavior in a more

detailed  way  than  the  standard  model  does.  Although  we

agree  with  this  point,  and  think  that  modeling  congestion

behavior for computer networks is a promising avenue for

future research, we here consider only the simplest textbook

case of congestion.

     We suppose that a representative user has a utility func-

tion u(xi)-D, where xi is the number of packets sent by user
_________________________________________
 35  The treatment is intended for economists; it is probably too terse for
non-economists.



                                       45

i and D is the total delay experienced by the user. The delay

depends on the total utilization of the network, Y  = X=K
             P  n
where  X  =     i=1  xi  is  the  total  usage  and  K  is  network

capacity.36    This  specification  implies  that  if  usage  X  is

doubled and capacity K is doubled, then network utilization

Y  = X=K and delay D(Y ) remain the same.

     If there is no congestion-based pricing, user i will choose

xi to satisfy the first-order condition37


                                 u0(xi) = 0:


The efficient utilization of the network maximizes the sum
                         P   n
of all users' utilities,     i=1  u(xi) - nD(X=K).  This yields

the n first-order conditions


                         u0(xi) - _n__KD0(Y ) = 0:


One way to achieve this efficient outcome is to set a conges-

tion price per packet of


                               p =  n___KD0(Y );                            (1)


so that user i faces the maximization problem


                      maxx   u(xi) - D(Y )) - pxi:
                          i

The first-order condition to this problem is


                         u0(xi) = p =  n___KD0(Y )                          (2)


which is easily seen to lead to the optimal choice of xi. The

price has been chosen to measure the congestion costs that

i's packets impose on the other users.
_________________________________________
 36  We could also make the utility of packets depend on the delay by writing
utility as u(xi; D). We choose the additively separable specification only
for simplicity.

 37  We assume that the user ignores the fact that his own packets impose
delay on his own packets; we can think of this effect as being built into the
utility function already.  There is no problem in relaxing this assumption;
the calculations just become messier.



                                       46

Optimal capacity expansion


Suppose now that it costs c(K) for capacity K  and that we

currently have some historically given capacity. Should the

capacity be expanded? The welfare problem is

                          X n
            W (K) = maxK        u(xi) - nD(Y ) - c(K):
                           i=1


Since xi is already chosen so as to maximize this expression,

the envelope theorem implies that



                   W 0(K) = nD0(Y ) X____K2- c0(K):



Substituting from equation (1)



                        W 0(K) = p X___K- c0(K):                            (3)



Suppose  that  the  marginal  cost  of  capacity  expansion  is

a  constant,  cK    =  c0(K).    Then  we  see  that  W 0(K)  is

positive if and only if pX - cK  K  > 0.  That is, capacity

should expanded when the revenues from congestion fees

exceed the cost of providing the capacity.



A competitive market for network services


Suppose  that  there  are  several  competing  firms  providing

network  access.   A  typical  producer  has  a  network  with

capacity  K  and  carries  X  packets,  each  of  which  pays  a

packet  charge  of  p.   The  producer's  operating  profits  are

pX - c(K).

     Let p(D) be the price charged by a provider that offers

delay D. In general, if the delay on one network is different

than  on  another  the  price  will  have  to  reflect  this  quality


                                       47

difference. The utility maximization problem for consumer i

is to choose which network to use and how much to use it:


                       maxx   u(xi) - D - p(D)xi
                           i;D

which has first-order conditions

                            u0(xi) - p(D)       = 0


                            -1 - p0(D)xi        = 0:

The first equation says that each user will send packets until

the value of an additional packet equals its price. The second

equation  says  that  the  user  will  choose  a  network  with  a

level of delay that such that the marginal value to the user of

additional delay equals the marginal cost of paying for the

delay (by switching suppliers). Adding up this last first-order

condition over the consumers yields


                              n = -p0(D)X:                                  (4)


     A  competitive  producer  offering  delay  D(Y )  wants  to

choose capacity and price so as to maximize profits, recog-

nizing that if it changes its delay the price that it can charge

for access will change. The profit maximization problem is


                        maxX;K p(D(Y ))X - c(K);


which gives us first-order conditions

                         p0(D)D0(Y )Y  + p(D)          = 0
                                                                            (5)
                    -p0(D)D0(Y )Y 2 - c0(K)            = 0:

Combining these two conditions and using equation (4) gives

us two useful expressions for p(D):


                            p(D)    =  n___KD0(Y )
                                                    :
                                    = c0(K) K___X


                                       48

Comparing the first equation to (2) we see that the compet-

itive  price  will  result  in  the  optimal  degree  of  congestion.

Comparing the second equation to equation (3) we see that

competitive behavior will also result in optimal capacity.



Adding capacity


Suppose  now  that  a  competitive  firm  is  trying  to  decide

whether  to  add  additional  capacity  K.   We  consider  two

scenarios. In the first scenario, the firm contemplates keeping

X fixed and simply charging more for the reduction in delay.

The amount extra it can charge for each packet is


                    _dp__ K = -p0(D)D0(Y ) X____K:
                    dK                     K2


Using equation (5) this becomes


                                     _p__K:
                                     K


Since the firm can charge this amount for each packet sent,

the total additional revenue from this capacity expansion is



                                    p X___KK:



This revenue will cover the costs of expansion if

                               ~               ~

           p X___KK - c0(K)K =   p X___K- c0(K)     K   0;



which is precisely the condition for social optimality as given

in equation (3).

     Consider  now  the  second  scenario.   The  firm  expands

its  capacity  and  keeps  its  price  fixed.   In  a  competitive

market it will attract new customers due to the reduction in

delay.  In  equilibrium  this  firm  must  have  the  same  delay


                                       49

as other firms charging the same price.  Suppose that in the

initial equilibrium X=K  = Y .  Then the additional number

of  packets  sent  must  satisfy  X  =  Y K:  It  follows  that  the

increase in in profit for this firm is given by

                               ~               ~

               pY K - c0(K)K =   p X___K- c0(K)     K:



Again we see that capacity expansion is optimal if and only

if it increases profits.

     The relationship between capacity expansion and conges-

tion pricing was first recognized by Mohring and Hartwize

(1962) and Strotz (1978). Some recent general results can be

found in Arnott and Kraus (1992b, 1992a).

                                       50

Appendix  2:  An  hypothetical  one-node  backbone  with

smart market


     Implementing any pricing scheme for backbone services

will  require  changes  to  user  applications,  host  operating

systems,  and router algorithms.  Very little work has been

done  on  the  software  and  protocol  changes  necessary  to

support efficient pricing.38  To illustrate the types of changes

that  will  be  necessary,  we  shall  briefly  describe  how  our

smart market might be implemented in a very simple case.

     Consider a simple network fragment: two host machines,

each with multiple users, each connected to a separate local

area network.  The two LANs are connected by a backbone

with a single switch (which admittedly doesn't have much

work to do!).  Users have applications that send packets to

each other.  How would the smart market work if users are

sending each other a steady flow of packets that is sufficient

to cause congestion at the switch if all packets were admitted?



User application


Suppose user 1 on machine 1 (u11 ) is sending e-mail to user

1 on machine 2 (u12 ).  u11  needs to be able to set her bid

(maximum willingness to pay) for the packets that make up

her e-mail message. However, she prefers not to think about

a bid for every message since she usually puts the same, very

low priority price on e-mail. Thus, the e-mail software needs

to provide hooks for a user to set a default bid price, and to

override the default when desired.
_________________________________________
 38  A draft technical report has proposed some semantics and a conceptual
model for network usage accounting, but this has not become a standard,
nor does it deal with billing or cost allocation; see C. Mills (1991).  See
Braun and Claffy (1993) for a detailed discussion of some of the problems
facing usage accounting.



                                       51

User system


The  host  machine  must  handle  some  new  tasks  through

systems software. First, the e-mail is packetized with one new

piece of information loaded into the header: the bid price.39

Also,  since  this  is  a  multiuser  machine  and  the  network

only recognizes machine (IP) addresses, not user names, the

host machine must create a record in an accounting database

that records the user name, number of packets sent, and the

packet identification number. It is not possible to record the

price for the packets yet because of the design of the smart

market: the user specifies her maximum willingness to pay,

but the actual price for each packet may (and typically will)

be lower.  However, since the TCP protocol offers positive

acknowledgement of each packet, the acknowledging packets

that are returned can contain the actual price charged so that

the host database can record user-specific charges.



Local area network


It may be desirable to implement some hooks in the local

organization  network,  before  the  packet  reaches  the  back-

bone.40    For  example,  organization  policy  may  want  to

impose a ceiling on bids to restrict the maximum price that

users  volunteer  to  pay.   Also,  billing  from  the  backbone

provider may be only to the organization level since the IP

address  of  host  machines  identifies  only  a  station,  not  the
_________________________________________
 39  It would be natural to use the priority field to contain the bid price.


 40  In  practice  there  may  be  several  levels  of  interconnected  network
between the user and the backbone: departmental, organization, regional,
national. What we say here about a single local network should generally
apply at each such level.



                                       52

responsible  users.  It  may  be  that  backbone  providers  will

provide bills that itemize by host IP address; the organization

may want to record packets sent by each host, as well as the

price extracted from the acknowledgement return.

     In this example we assume that the local network is not

imposing its own charges on top of the backbone charges. If

local pricing is desired to allocate locally congested resources

(as we suspect if often will be for large organizations), the

tasks identified below for the backbone must also be carried

out by the LAN.
Backbone


As  a  packet  reaches  the  backbone  router,  its  bid  price  is

compared to the current smart market price for admission. If

the bid is too low, a message (presumably implemented in

the ICMP protocol) is returned to the user with the packet

number, user's bid and the current price.  If the bid exceeds

the admission price, then the packet is admitted and routed.

     Every  packet  is  checked  for  its  bid,  but  to  control  the

transactions  costs  of  pricing,  accounting,  and  billing  we

assume that only 1 of every N packets is sampled for further

processing.  A  copy  of  the  header  of  the  sampled  packets

is diverted to a separate CPU, where it is used for several

functions.

     One task is to update the state of demand on the backbone.

Packets with bids come in over time; it will be necessary to

aggregate packets over some window (the width of which

could be time- or event-driven) to construct the ``current''

state of demand.  When a newly sampled packet arrives, it


                                       53

is  added  to  the  history  window  of  bids,  and  a  stale  bid  is

removed.41

     The sampled packet is logged to the accounting database:

the  current  price  times  N  (since  the  packet  represents  on

average  1=N th  of  those  sent  by  a  particular  user)  and  the

billing identification information. Periodically the backbone

provider will prepare and deliver bills.

     Periodically the smart market price would be recalculated

to  reflect  changes  in  the  state  of  demand.   A  new  price

might be event-driven (e.g., recalculated every time a new

N th packet arrives, or less frequently) or time-driven (e.g.,

recalculated  every  T  msecs).   The  new  price  would  then

be sent to the gatekeeper subsystem on the router, and in a

network with multiple nodes possibly broadcast to the other

nodes.42



``Collect calls'': Pricing proxy server packets


We  have  assumed  so  far  that  the  originator  of  a  packet  is

the party to be billed.  Many of the most important Internet

services  involve  packets  that  are  sent  by  one  host  at  the

request  of  a  user  on  another  host.   For  example,  ftp  file

transfers  and  gopher  information  services  take  this  form;

these are currently the first and seventh largest sources of

bytes transferred on the NSFnet backbone (Braun and Claffy

(1993)).   Clearly  most  services  will  not  offer  to  pay  the

network charges for any and all user requests for data.  We
_________________________________________
 41  The market algorithm would account for the fact that each packet was
a representative for N other packets assumed to have the same bid.

 42  We comment below on some of the issues for implementing a smart
market in a multiple node environment.



                                       54

need something like collect calls, COD, or bill-to-recipient's-

account, or all of the above.

     There are at least two straightforward methods to charge

the  costs  back  to  the  responsible  party.   A  traditional  ap-

proach would have users obtain accounts and authorization

codes that permit the proxy server to use an external billing

system for charges incurred by user requests; this is the way

that  many  current  commercial  information  services  (e.g.,

Compuserve) are billed.

     However, the growth of the Internet has been fueled by

the vast proliferation of information services. It is implausible

to think that a user would be willing to obtain separate charge

accounts with every service; it would also be inefficient to

have the necessary credit and risk management duplicated by

every proxy server provider. A more advanced method that

fits in well with the scheme we have described is to allow for

billing directly back to the user's backbone usage account.

     To implement a system of bill-to-sender would require

some further work, however.  The user's application (client

software) would presumably have to allow the user to specify

a maximum price for an entire transaction which could be

included  in  the  request  for  service,  since  it  will  often  be

impossible to anticipate the number of packets that are being

requested.   The  server  could  then  send  the  packets  with

a  flag  set  in  the  packet  header  that  indicates  the  charges

are to be levied against the destination IP address,  not the

source.    However,  to  make  such  a  system  feasible  will

require authentication and authorization services. Otherwise,

unscrupulous  uses  could  send  out  packets  that  were  not

requested by the recipients but charge them to the destination


                                       55

address;  likewise  malicious  pranksters  could  modify  their

system software to generate forged requests for data that is

unwanted by but charged to another user.43


_________________________________________
 43  There may also be a way to steal network services by having them
billed to another user, but we haven't figured out how to do that yet.



                                       56

                                 References


Almquist, P. (1992). Type of service in the internet protocol
         suite. Tech. rep. RFC 1349, Network Working Group.

Anonymous (1986).  Stratacom, inc. introduces `packetized
         voice system'. Communications Week, 2.

Arnott, R., de Palma, A., and Lindsey, R. (1990). Economics
         of a bottleneck. Journal of Urban Economics, 27, 111-
         -130.

Arnott,  R.,  and  Kraus,  M.  (1992a).    Financing  capacity
         on the bottleneck model.  Tech. rep.,  Department of
         Economics, Boston College.

Arnott,  R.,  and  Kraus,  M.  (1992b).     Self-financing  of
         congestible facilities in a dynamic environment. Tech.
         rep., Economics Department, Boston College.

Braun, H.-W., and Claffy, K. (1993).   Network analysis in
         support  of  internet  policy  requirements.   Tech.  rep.,
         San Diego Supercomputer Center.

C.  Mills,  D.  Hirsh,  G.  R.  (1991).     Internet  accounting:
         Background. Tech. rep. RFC 1272, Network Working
         Group.

Cerf,  V.  G.  (1993).    Core  protocols.   In  Internet  System
         Handbook. Addison Wesley, Reading, MA.

Claffy,  K.  C.,  Polyzos,  G.  C.,  and  Braun,  H.-W.  (1992).
         Traffic characteristics of the t1 nsfnet backbone. Tech.
         rep. CS92-252, UCSD.  Available via Merit gopher in
         Introducing the Internet directory.

Cocchi,  R.,  Estrin,  D.,  Shenker,  S.,  and Zhang,  L. (1992).
         Pricing in computer networks:  Motivation,  formula-
         tion, and example.  Tech. rep., University of Southern
         California.

Estrin,  D.  (1989).   Policy  requirements  for  inter  adminis-
         trative  domain  routing.   Tech.  rep.  RFC1125,  USC
         Computer Science Department.

Faulhaber,  G.  R.  (1992).    Pricing  Internet:  The  efficient
         subsidy.   In  Kahin,  B.  (Ed.),  Building  Information
         Infrastructure. McGraw-Hill Primis.

Gerla, M., and Kleinrock, L. (1988).  Congestion control in
         interconnected lans. IEEE Network, 2(1), 72--76.


                                       57

Huber, P. W. (1987).  The Geodesic Network: 1987 Report
         on Competition in the Telephone Industry. U.S. Gov't
         Printing Office, Washington, DC.

K. Claffy, H.-W. B., and Polyzos, G. (1993). Application of
         sampling methodologies to wide-area network traffic
         characterization.  Tech. rep. Technical Report CS93-
         275, UCSD.

Kahin, B. (1992).  Overview: Understanding the NREN.  In
         Kahin, B. (Ed.), Building Information Infrastructure.
         McGraw-Hill Primis, NY.

Kleinrock,  L.  (1992).     Technology  issues  in  the  design
         of NREN.  In Kahin,  B. (Ed.),  Building Information
         Infrastructure. McGraw-Hill Primis.

Krol, E. (1992). The Whole Internet. O'Reilly & Associates,
         Inc., Sebastopol, CA.

MacKie-Mason, J., and Varian, H. (1993). Some economics
         of the internet. Tech. rep., University of Michigan.

Mohring, H., and Hartwize, M. (1962).  Highway Benefits:
         An  Analytical  Approach.    Northwestern  University
         Press, Evanston.

Postel,  J.  (1981).   Darpa  internet  program  protocol  speci-
         fication.  Tech.  rep.  RFC  791,  Information  Sciences
         Institute, University of Southern California.

Prue,  W.,  and  Postel,  J.  (1988).   A  queuing  algorithm  to
         provide type-of-service for ip links.  Tech. rep. RFC
         1046, USC Information Sciences Institute.

Roberts, L. G. (1974).  Data by the packet.  IEEE Spectrum,
         XX, 46--51.

Ruth, G., and Mills, C. (1992).  Usage-based cost recovery
         in internetworks.  Business Communications Review,
         xx, 38--42.

Shenker, S. (1993).  Service models and pricing policies for
         an integrated services internet.  Tech. rep., Palo Alto
         Research Center, Xerox Corporation.

Smarr, L. L., and Catlett, C. E. (1992).  Life after Internet:
         Making room for new applications. In Kahin, B. (Ed.),
         Building  Information  Infrastructure.    McGraw-Hill
         Primis.



                                       58

Strotz, R. (1978). Urban transportation parables. In Margolis,
         J. (Ed.), The Public Economy of Urban Communities.
         Resources for the Future, Washington, D.C.

Waldspurger, C. A., Hogg, T., Huberman, B. A., Kephart,
         J.  O.,  and  Stornetta,  W.  S.  (1992).   Spawn:  A  dis-
         tributed computational economy.  IEEE Transactions
         on Software Engineering, 18(2), 103--117.

Wilson,  R.  (1989).    Efficient  and  competitive  rationing.
         Econometrica, 57(1), 1--40.



                                       59

 




-----------------------------------------------------------------------

     This file passed through SEA OF NOISE, +1 203 886 1441...

                          SHARE & ENJOY!

-----------------------------------------------------------------------

