Distributed algorithms for extending the functional lifetime of wireless sensor networks

The functional lifetime of a wireless sensor network (WSN) is among its most important features and serves as an essential metric in the evaluation of its energy-conserving policies. Approaches for extending the lifetime of a wireless sensor node include using an on/off strategy on the sensor nodes and using a topology control algorithm on each node to regulate its transmission power. However, the need to keep the network functional imposes certain additional constraints on strategies for energy conservation. A sensing constraint imposes that the sensing tasks essential to the functionality of the WSN are not compromised. A communication constraint similarly imposes that communications essential to an application on the network remain possible even as battery resources deplete on the nodes. This dissertation presents new distributed algorithms for energy conservation under these two classes of constraints: sensing constraints and communication constraints. One sensing constraint, called the representation constraint in this dissertation, is the requirement that active (on) sensor nodes are evenly distributed in the region of interest covered by the sensor network. This dissertation develops two essential metrics which together allow a rigorous quantitative assessment of the quality of representation achieved by a WSN and presents analytical results which bound these metrics in the common scenario of a planar region of arbitrary shape covered by a sensor network deployment. The dissertation further proposes a new distributed algorithm for energy conservation under the representation constraint. Simulation results show that the proposed algorithm is able to significantly improve the quality of representation compared to other related distributed algorithms. It also shows that improved spatial uniformity has the welcome side-effect of a significant increase in the functional lifetime of a WSN. One communication constraint, called the connectivity constraint, imposes that the network remains connected during its functional life. The connectivity required may be weak (allowing unidirectional communication between nodes) or strong (requiring bidirectional link layer communication between each pair of communicating nodes). This dissertation develops new distributed topology control algorithms for energy conservation under both the strong and the weak connectivity constraint. The proposed algorithm for the more ideal scenario of the weak connectivity constraint uses a game-theoretic approach. The dissertation proves the existence of a Nash equilibrium for the game and computes the associated price of anarchy. Simulation results show that the algorithms extend the network lifetime beyond those achieved by previously known algorithms.Ph.D., Computer engineering -- Drexel University, 201