Pricing Multicast Network Services
Shrinivas, V Prasanna
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Multicast has long been considered an attractive service for the Internet for the provision of multiparty applications. For over a decade now multicast has been a proposed IETF standard. Though there is a strong industry push towards deploying multicast, there has been little multicast deployment by commercial Internet Service Providers (ISPs) and more importantly most end-users still lack multicast capabilities. Depending on the underlying network infrastructure, the ISP has several options of implementing his multicast capabilities. With significantly faster and more sophisticated protocols being designed and prototyped, it is expected that a whole new gamut of applications that are delay sensitive will come into being. However, the incentives to resolve the conflicting interests of the ISPs and the end-users have to be provided for successful implementation of these protocols. Thus we arrive at the following economic questions: What is the strategy that will enable the ISP recover his costs ? How can the end-user be made aware of the cost of his actions ? Naturally, the strategies of the ISP and the end-user depend on each other and form an economic game. The research problems addressed in this thesis are: A pricing model that is independent of the underlying transmission protocols is prefered. We have proposed such a pricing scheme for multicast independent of the underlying protocols, by introducing the concept of pricing points* These pricing points provide a range of prices that the users can expect during a particular time period and tune their usage accordingly. Our pricing scheme makes both the sender and receiver accountable. Our scheme also provides for catering to heterogeneous users and gives incentive for differential pricing. We explore a number of formulations of resource allocation problems arising in communication networks as optimization models. Optimization-based methods were only employed for unicast congestion control. We have extended this method for single rate multicast. We have also devised an optimization-based approach for multicast congestion control that finds an allocation rate to maximize the social welfare. Finally we also show that the session-splitting problem can also be cast as an optimization problem. The commonly used "max-min" fairness criteria suffers from serious limitations like discriminating sessions that traverse large number of links and poor network utilization. We provide an allocation scheme that reduces discrimination towards multicast sessions that traverse many links and also improves network utilization.