A Distributed Algorithmic Framework for Coverage Problems in Wireless Sensor Networks

Akshaye Dhawan, Sushil K. Prasad

OAI: oai:digitalcommons.ursinus.edu:math_comp_fac-1001

One of the key challenges in Wireless Sensor Networks (WSNs) is that of extending the lifetime of the network while meeting some coverage requirements. In this paper, we present a distributed algorithmic framework to enable sensors to determine their sleep-sense cycles based on specific coverage goals. The framework is based on our earlier work on the target coverage problem. We give a general version of the framework that can be used to solve network/graph optimization problems for which melding compatible neighboring local solutions directly yields globally feasible solutions such as the maximal independent set problem. We also apply this framework to several variations of the coverage problem, namely, target coverage, area coverage and k-coverage problems, to demonstrate its general applicability. Each sensor constructs minimal cover sets for its local coverage objective. The framework entails each sensor prioritizing these local cover sets and then negotiating with its neighbors for satisfying mutual constraints. We employ a dependency graph model that can capture the interdependencies among the cover sets. Detailed simulations are carried out to further demonstrate the resulting performance improvements and effectiveness of the framework. These show an improvement of between 10%-20% over existing algorithms.

wireless sensor networks scheduling Energy efficiency maximum lifetime distributed algorithms localized algorithms maximum independent set Computer Sciences Physical Sciences and Mathematics