Swarm intelligence approaches for cover scheduling problem in wireless sensor networks

Abstract

Wireless sensor networks (WSNs) are getting more and more attention these days. Already, innumerable approaches have been proposed to solve various problems in WSNs. In this paper, we have proposed two swarm intelligence approaches, viz. artificial bee colony (ABC) algorithm and invasive weed optimisation (IWO) algorithm for the cover scheduling problem in WSNs where coverage breach is allowed either due to technical constraints or deliberately. The objective of the wireless sensor network cover scheduling problem (WSN–CSP) is to schedule the covers of sensors in such a manner so that the longest target breach is minimised. The WSN–CSP is an NP–Hard problem and is relatively under–studied. ABC algorithm is based on intelligent foraging behaviour of honey bee swarms, whereas IWO algorithm is based on colonising behaviour of weeds. For further improving the results obtained through ABC and IWO approaches, we have also devised a local search. Computational results show the effectiveness of our proposed approaches in comparison to a genetic algorithm and a problem specific heuristic available in the literature.