Abstract-We consider the situation where N nodes share a common access point. With each node i there is an associated buffer and channel state that change in time. Node i dynamically chooses both the power and the admission control to be adopted so as to maximize the expected throughput, which depends on the actions and states of all the players, given its power and delay constraints. The information structure that we consider is such that each player knows the state of its own buffer and channel and its own actions. It does not know the states of, and the actions taken by other players. Using Markov Decision Processes we analyze the single player optimal policies under different model parameters. In the context of the stochastic games we study the equilibria of the N player scenario.

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A major contribution of biology to competitive decision making is the area of evolutionary games. It describes the evolution of sizes of large populations as a result of many local interactions, each involving a small number of randomly selected individuals. An individual plays only once; it plays in a one shot game against another randomly selected player with the goal of maximizing its utility (fitness) in that game. We introduce here a new more general type of games: a Stochastic Evolutionary Game where each player may be in different states; the player may be involved in several local interactions during his life time and his actions determine not only the utilities but also the transition probabilities and his life duration. This is used to study a large population of mobiles forming a sparse ad-hoc network, where mobiles compete with their neighbors on the access to a radio channel. We study the impact of the level of energy in the battery on the aggressiveness of the access policy of mobiles at equilibrium. We obtain properties of the ESS (Evolutionary Stable Strategy) equilibrium which, Unlike the Nash equilibrium concept, is robust against deviations of a whole positive fraction of the population. We further study dynamical properties of the system when it is not in equilibrium.

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Abstract-The throughput of AIMD protocols in general and of TCP in particular, has been computed in many existing works by modeling the round-trip time as a constant and thus replacing the round-trip time by its expectation. There are however many scenarios in which the delays of packets vary, causing a variation of the round-trip time. Many typical scenarios occur in wireless and mobile networks. We propose in this paper an analytical model that accounts for the variability of delay, while computing the throughput of an AIMD protocol. We derive a closed-form expression for the throughput, that illustrates the impact of the variability of delay. We show by analysis and simulation, that an increase in the variability of delay improves the performance of an AIMD protocol. Thus, an analytical model that only considers the average delay could underestimate the performance of an AIMD protocol in scenarios where delay is variable.