A Game-Theoretic Approach to Efficient Power Management in Sensor Networks

Abstract

Wireless sensor networks pose numerous fundamental coordination problems. For example, in a number of application domains including homeland security, environmental monitoring, and surveillance for military operations, a network's ability to efficiently manage power consumption is extremely critical because direct user intervention after initial deployment is severely limited. In these settings, limited battery life gives rise to the basic coordination problem of maintaining coverage while maximizing the network's lifetime. In this paper, we propose a distributed scheme for efficient power management in sensor networks that is guaranteed to identify suboptimal topologies in an online fashion. Our scheme is based on a general (game-theoretic) mathematical structure that induces a natural mapping between the informational layer and the physical layer. We provide sufficient conditions for the convergence of the algorithm to a pure Nash equilibrium and characterize the performance of the algorithm in terms of coverage. We also present encouraging performance results on a MicaZ testbed as well as on large-scale topologies (obtained via simulation).

An architectural view of game theoretic control

“…Thus, requiring the structure of potential games enforces additional constraints on utility and learning design, but also deconstrains at a higher level by allowing modularization. Though this layered architecture was not explicitly used in prior work, the modularization provided by potential games underlies many successful examples of game-theoretic control [9,23,30,38]. The change in perspective provided by this architectural view is not simply superficial; it highlights that the utility and learning designs in these papers can be 'mixed and matched' while still obtaining the same performance.…”

“…We focus on potential games because many recent applications of game-theoretic control have relied on potential games, e.g., [9,23,30,38]. A key reason that potential games are a powerful choice for the interface is that they are a highly studied class of games in the economics literature, e.g., [16,42,52,59,66] and so there is a large literature of results that can be used in the context of game-theoretic control for both utility and learning design.…”

“…A variety of resource allocation problems such as power control and coverage problems in sensor networks [9,38], wireless access point assignment and frequency selection [28], outbreak detection [32], path planning [56], clustering [44], and influence maximization [29] all have submodular welfare functions.…”

“…However, in many modern applications, these centralized algorithms are not applicable and/or desirable, due to their poor reliability, efficiency and scalability. As a result, increasingly, resource allocation is a problem that needs to be solved in a distributed, decentralized manner, e.g., power control and frequency selection problems in wireless networks [5,7,9,18,28] and coverage problems in sensor networks [10,38]. Resultantly, there is a large and growing literature that focuses on developing distributed resource allocation protocols.…”

“…Game-theoretic resource allocation designs are increasingly popular in a variety of wireless and sensor network applications, e.g., channel access control in wireless networks [7,28], coverage problems in sensor networks [10,38], and power control in both [5,9,18]. A comprehensive survey of applications can be found in [6].…”