Distributed Algorithms for Lifetime of Wireless Sensor Networks Based on Dependencies Among Cover Sets

Abstract

We present a new set of distributed algorithms for scheduling sensors to enhance the total lifetime of a wireless sensor network. These algorithms are based on constructing minimal cover sets each consisting of one or more sensors which can collectively cover the local targets.  Some of the covers are heuristically better than others for a sensor trying to decide its own sense-sleep status.  This leads to various ways to assign priorities to the covers. The algorithms work by having each sensor transition through these possible prioritized cover sets, settling for the best cover it can negotiate with its neighbors.   A local lifetime dependency graph consisting of the cover sets as nodes with any two nodes connected if the corresponding covers intersect captures the interdependencies among the covers. We present several variations of the basic algorithmic framework.  The priority function of a cover is derived from its degree or connectedness in the dependency graph - usually lower the better.  Lifetime improvement is 10% to 20% over the existing algorithms, while maintaining comparable communication overheads.   We also show how previous algorithms can be formulated within our framework.