Interconnection Agreements between Competing Internet Service Providers

Transcription

1 Proceedings of the 33rd Hawaii International Conference on System Sciences Interconnection Agreements between Competing Internet Service Providers Rajiv Dewan*, Marshall Freimer, and Pavan Gundepudi {dewan, freimer, gundepudpa}@ssb.rochester.edu Simon School, University of Rochester, Rochester, NY 467. *Phone: , *Fax: Abstract: The wide area networks, which make up the infrastructure of the Internet, connect at peering points that are either publicly or privately owned. Public peering points have become increasingly congested and offer poor connectivity and availability. Consequently, private agreements for increased interconnection capacity between network firms have become common. These agreements affect the quality of service and profits of the networks in different ways. To examine these issues, we construct a model of the economy in which two networks with different number of hosts are serving the same region and customers pick the network that offers them the most net benefit. We find that the network that hosts more content prefers a lower interconnection capacity than the other network. Consumers on that network see an increase in the congestion of their home network as a larger number of users from the other network gain easier access with an increase in interconnection capacity. On the other hand, consumers on the network with fewer hosts benefit greatly from increases in peering point capacity from private agreements. Introduction The Internet wide area networking services are provided by a number of private firms that own large capacity links and switching centers. Such high capacity wide area networks are called backbone networks. These networks connect at peering points to provide traffic transfer and seamless interconnection and interoperation. Initially, the National Science Foundation set up three public peering points, in Chicago, Palo Alto, and Pennsauken, NJ. It later added two more industry run sites, called Metropolitan Access Exchanges, East in Vienna, VA and West in San Jose, CA. The networks exchanged traffic at these public peering points [Leiner, Cerf, et al, 998], [Yang, 998]. Public peering, though successful at tying the Internet together, has not been a successful solution. For starters, there are just a few public peering or traffic exchange points and they may not match the reach of the networks. For example, most of the major networks have points of presence in cities such as New York City and Boston. And yet, the closest public peering site is in Pennsauken, New Jersey. Consequently, traffic from a network site in Boston to another network s site in the same city may have to be exchanged in New Jersey. This network disadvantage is further exacerbated by the bad economics of public peering. No single network has the incentive to invest in public peering points and yet they all benefit from them. A network investing in a high capacity line into a public peering point gets all the costs but only some of the /00 $0.00 (c) 000 IEEE

2 Proceedings of the 33rd Hawaii International Conference on System Sciences benefits. This creates a disincentive to invest in higher capacities for public peering [Winkleman, 998]. Further, because of a lack of pricing of traffic at public peering points, the networks tend to overuse these to the point where the congestion becomes excessive [Barrett, 998]. So we have the convergence of two negative economic phenomena at these public exchanges: lack of willingness to invest in capacity and overuse. Both of these make public peering unsatisfactory. Networks get around the public peering or exchange bottlenecks by forming private peering arrangements that are governed by bilateral agreements. These agreements vary considerably [Bailey, 997], [Srinagesh, 997]. While some are on a quid pro quo basis, permitting free exchange of traffic, others specify a charge for net flow of traffic. Yet others require the peering network to have comparable network size and scope (ex. Fiber-Network Solutions), network capacity (ex. Uunet, see Yang, 998), and geographic coverage (ex. IBM s backbone now owned by AT&T, see ). In this paper we focus on private peering agreements between firms that provide Internet backbone services while competing for customers in the same location. In an earlier work we have examined private peering arrangements between firms in separate regions [Dewan, Freimer and Gundepudi, 999]. Private interconnection improves the quality of service for all customers by reducing peering point delays. The slow public peering point is replaced by a private connection with higher effective capacity. However this improvement in service is accompanied by an increase in traffic within the backbone networks. Hence, a customer of the service experiences a decrease in peering point delay but an increase in backbone-network delays. These competing effects complicate the choice of capacity of private interconnection. Interconnection agreements also affect the way in which backbone network firms compete for customers. Firms differentiate themselves by hosting different content providers. The value of differentiation for maintaining profits in a competitive marketplace is reduced by high capacity interconnections. The combination of congestion effects and differentiation strategies determine the value of interconnection to each of the firms in the agreement. We present a model of two interconnected networks that host different proportions of content providers. Both the networks and the interconnection point are sources of congestion. Customers incur delay costs when accessing content on the two networks. We find that the larger backbone network (with more customers and hosts) prefers to have a lower capacity for the private interconnection than the smaller backbone network. We also find that the total surplus of all customers increases monotonically with interconnection capacity. However, the profits of the firms, even without considering the cost of interconnection, eventually decrease with increases in interconnection capacity as congestion externalities make the customers less willing to pay for services. The total surplus of customers and firms is unimodal in interconnection capacity in the sense that it has a unique maximum point when plotted against the interconnection capacity. In fact, the socially optimal interconnection capacity lies between the capacity choices of the two backbone services providers. In the next section we model the economics of interconnected networks. In section 3 we examine private peering /00 $0.00 (c) 000 IEEE

3 Proceedings of the 33rd Hawaii International Conference on System Sciences Modeling Competing Interconnected Networks To simplify the analysis, we consider two networks owned by firms Network and Network, respectively, that operate in the same area and compete for customers. They host α and α proportions of content providers, respectively. Let p and p be the prices charged by the two firms, respectively, for Internet access services. Each customer has a reservation price of r for getting Internet services. The net surplus of a customer of a network charging a fee of p and experiencing a delay of d is r p c d where c is delay cost per unit time. The customers are heterogeneous in their tolerance of delay, i.e., they differ in c. The customer chooses whether or not to get Internet services and he picks the network that offers him the highest positive surplus. Let m be the number of customers that choose to get Internet services from Network and m be the corresponding number for Network. This model is presented in Reitman (99) in a relevant context where firms selling a product with congestion externalities to a heterogeneous population of customers have an incentive to offer differentiated levels of quality. However, we extend it to study how interconnection agreements affect the competition between the firms for customers. Firms here also differentiate on the basis of the proportion of content providers they host. In a related paper, Baake and Wichmann (999) investigate the decision about a bilateral peering arrangement between two commercial providers who are in Cournot competition. Let the traffic in the two networks and the peering point be: t = α ( m t + m ) µ = ( α)( m t p = ( α) mµ + α mµ + m ) µ () where µ is the capacity of the two networks and the interconnection point. The peering point gets the cross traffic between networks. Assuming that the traffic arrival and service to each network and the peering point follow the M/M/ queuing discipline and that the assumptions needed to make the interconnected queues a Jackson network hold, the delays incurred by customers of the two networks are: d = α + ( α ) + µ t µ t t p d r p p = ( α ) + α + µ t µ t µ $ Surplus to customer of Network Slope = d p t p Slope = d () Net Cust. c Net c Customers 0 Surplus to customer of Network Figure : Market Segmentation between Networks Consider Figure to determine the market segment for each network. The figure plots consumer surplus from using the two networks for customers with delay cost rate c c /00 $0.00 (c) 000 IEEE 3

4 Proceedings of the 33rd Hawaii International Conference on System Sciences along the X-axis. Network () charges a higher (lower) price but offers a lower (higher) delay. This kind of equilibrium has been observed in other markets. For instance, Png and Reitman [994] find that a gasoline station can charge more per gallon of gasoline than a nearby station if it offers less congested facilities. Referring again to Figure, customer with a delay cost rate of c is indifferent between the two networks and the customer with a delay cost rate of c 0 is indifferent between getting service from Network and getting no service at all. Note that: m m = c + m p p = d d = c 0 r p = d (3) Substituting () and () into (3) we get two simultaneous equations in m and m, the number of customers. Let m (p, p ) and m (p, p ) be the solutions to the simultaneous equations. The profits for the two networks are p m (p, p ) and p m (p, p ), respectively. Each network picks a price to maximize its profits given the price set by the other network. This gives rise to an economic game whose Nash we study. 3 Private Network Interconnection Private network interconnection offers a way to bypass the congested public peering points. As discussed earlier, the public good nature of the public peering points results in under investment in capacity. Private peering arrangements offer the possibility of increasing the peering capacity for mutual benefit. This is explored next. The profits of the two networks, on a per customer basis, as a function of is shown in Figure. Parameter α =.80, i.e., network has 80% of the hosts. Other parameters are r = 6, k = µ =. $ Profit of network with 80% of hosts. Profit of network with 0% of hosts. Figure : Impact of Peering Point Capacity on Network Profits. Firstly, note that the profit curves are unimodal in shape. This is a result of a number of competing effects: An increase in peering point capacity reduces the dead weight loss that the customers incur from peering point delays. This makes them willing to pay more. This increases profits. Increased peering point traffic results in increased network traffic and delays within the two networks. This decreases profits. Increased peering point capacity makes the two networks similar to the customers. A customer of any one of the two networks can seamlessly and without much additional delay access the other network. This reduces the differentiation between the two networks and in the competitive situation, reduces their profits. Secondly, in Figure, note that if the /00 $0.00 (c) 000 IEEE 4

5 Proceedings of the 33rd Hawaii International Conference on System Sciences networks could pick the peering point capacity, then Network would pick = 0.38 while Network would pick = 0.6. This difference in choices of peering point capacity is significant and complicates private peering arrangements. Payments in Private Agreements Tandem queuing systems, like the one we have modeled, are susceptible to having bottlenecks in heavy traffic. This implies that if each network provides resources to form the private interconnection and they pick the capacity of their part of the link then a good approximation for determining queuing delays is to just use the lower capacity of the peering links chosen by the two networks. Hence the network that chooses a lower capacity, Network in this case, dominates. So what can Network do to alleviate this situation? It can offer Network an incentive or a payment to make a different choice for its part of the private interconnection. In this case, the Network could make a take or leave it offer where it picks a peering point capacity that is larger than Network s free choice and such that the absolute slopes of the profit curves are equal. Network will offer a payment equal to the decrease in Network s profit and keep the rest of the gain for itself. This is shown in Figure 3. This is just one example of a mechanism to improve peering point agreements. Take or leave it offers by Network and other bargaining solutions are also possible. Reports of private peering agreements indicate that it is not uncommon to have a fee based on traffic imbalance. Indeed, we find that unless the peering point has a very low effective capacity, Network customers are the primary instigators of peering point traffic. This is illustrated in Figure 4 in which the traffic into the peering point from the two networks is plotted against peering point capacity. Peering Point Traffic Traffic from Network Traffic from Network Figure 4: Traffic into the Peering Point $ Net Profit Net Profit Payment by Network to Network Gain in profits for Network Figure 3: Network pays Network to pick higher peering capacity Impact on Consumers Examining the consumer surplus plotted in Figure 5 provided insight into the impact of private interconnection agreements on consumers. Private agreements increase the peering point capacity from the low effective capacity of the public peering points. First consider the customers of Network the network with more hosts. As the peering point capacity increases from a low value, the consumers benefit from speedier access to content hosted on Network. However, the /00 $0.00 (c) 000 IEEE 5

6 Proceedings of the 33rd Hawaii International Conference on System Sciences traffic and resultant congestion in Network from Network traffic is increasing. Eventually, the bottleneck for Network customers shifts from the peering point to network itself and this results in reduced surplus for Network customers. sum of network profits and consumer surpluses. This is illustrated in Figure 6. We note that the total surplus is maximized at a peering point capacity that is in between the low choice of Network and the higher choice of Network. So neither of the two networks would pick the socially optimal Total Consumer Surplus Total for Net Consumers $ Total for Net Consumers Total Social Welfare (Profits + Consumer Surpluses) Network Profit µ Network Profit Figure 5: Total Surplus for Consumers in Each Network Network customers get most of the content from hosts on Network. Improvements in peering point capacity from private agreements increases their surplus. Since, only a few hosts are on Network, it does not have the congestion problem that Network does. This brings up an interesting observation: customers in the network with fewer hosts do better than a network with more content hosting as private agreements get more common. Social Policy Implications An increase in peering point capacity from private agreements affects the two networks and their consumers differently. As we have explored above, the network with a larger number of hosts prefers a lower capacity than the network with smaller number of hosts. Consumers on Network also prefer a smaller capacity but consumers on Network prefer as great an interconnection as possible. This difference in value of interconnection makes it useful to examine the total surplus Figure 6: Socially Optimal Peering Point Capacity interconnection capacity. Internet backbone consolidations increase the variation in hosting and network sizes. Four of the top six backbone networks have undergone consolidation within the last year. Cable and Wireless acquired the MCI backbone, Bell Atlantic is acquiring GTE s backbone network, AT&T has bought all of IBM s global backbone assets, and Worldcom s UUnet acquired AOL s and CompuServe s backbone networks. These consolidations create a lopsided distribution of hosts and increase the difficulty in coming to private interconnection agreements. 4 Conclusions Private peering agreements between Internet backbone service providers are becoming common. These agreements result in a private interconnection at higher capacity than the public peering point. An increase in interconnection capacity affects the traffic /00 $0.00 (c) 000 IEEE 6

7 Proceedings of the 33rd Hawaii International Conference on System Sciences not only through the interconnection point but also the traffic in the networks, especially in networks that host a greater amount of content. Consequently, firms that host a greater amount of content do not prefer to increase the peering point capacity to the level desired by connecting networks. Further, the traffic through the peering point and into the networks is not balanced. Typically, the traffic triggered by hits by consumers on the network with fewer hosts is greater than the traffic from the other network. These differences make it harder to achieve a gratis peer traffic exchange agreement. Economics by McKnight, L.W. and Bailey, J.P., Cambridge, MIT Press, Winkleman, J., Getting connected, America s Network, Aug. 5, Yang, C., How the Internet works: All you need to know, BusinessWeek, July 998. References. Baake, Pio, and Wichmann, Thorsten, (999), "On the Economics of Internet Peering," Netnomics, vol., pp Bailey, J.P., "The economics of Internet interconnection agreements" in Internet Economics by McKnight, L.W. and Bailey, J.P., Cambridge, MIT Press, Barrett, R., Peering into the future, Interactive Week, Dec. 7, Dewan, R.M., Freimer, M., and Gundepudi, P., Evolution of Internet Infrastructure in the st Century: The role of private interconnection agreements, forthcoming in Proceedings of ICIS, Charlotte, NC, Leiner, B.M., Cerf, V.G., et. al, A brief history of the Internet, Png, I.P.L., and Reitman, D., Service time competion, The Rand Journal of Economics, Winter Srinagesh, P., "Internet cost structures and interconnection agreements" in Internet /00 $0.00 (c) 000 IEEE 7