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We study how protocol design for various functionalities within a communication network architecture can be viewed as a distributed resource allocation problem. This involves understanding what resources are, how to allocate them fairly, and perhaps most importantly, how to achieve this goal in a distributed and stable fashion. We start with ideas of a centralized optimization framework and show how congestion control, routing and scheduling in wired and wireless networks can be thought of as fair resource allocation. We then move to the study of controllers that allow a decentralized solution of this problem. These controllers are the analytical equivalent of protocols in use on the Internet today, and we describe existing protocols as realizations of such controllers. The Internet is a dynamic system with feedback delays and flows that arrive and depart, which means that stability of the system cannot be taken for granted. We show how to incorporate stability into protocols, and thus, prevent undesirable network behavior. Finally, we consider a futuristic scenario where users are aware of the effects of their actions and try to game the system. We will see that the optimization framework is remarkably robust even to such gaming.

In this paper, we examine how transit and customer prices and quality of service are set in a network consisting of multiple ISPs. Some ISPs may face an identical set of circumstances in terms of potential customer pool and running costs. We examine the existence of equilibrium strategies in this situation and show how positive profit can be achieved using threat strategies with multiple qualities of service. It is shown that if the number of ISPs competing for the same customers is large then it can lead to price wars. ISPs that are not co-located may not directly compete for users, but are nevertheless involved in a non-cooperative game of setting access and transit prices for each other. They are linked economically through a sequence of providers forming a hierarchy, and we study their interaction by considering a multi-stage game. We also consider the economics of private exchange points and show that their viability depends on fundamental limits on the demand and cost.

We consider wireless ad hoc networks with a large number of users. Subsets of users might be interested in identical information, and so we have a regime in which several multicast sessions may coexist. We first calculate an upper-bound on the achievable transmission rate per multicast flow as a function of the number of multicast sources in such a network. We then propose a simple comb-based architecture for multicast routing which achieves the upper bound in an order sense under certain constraints. Compared to the approach of constructing a Steiner tree to decide multicast paths, our construction achieves the same order-optimal results while requiring little location information and no computational overhead.

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