Abstract
Abstract Maximum target coverage with minimum number of sensor nodes, known as an MCMS problem, is an important problem in directional sensor networks (DSNs). For guaranteed coverage and event reporting, the underlying mechanism must ensure that all targets are covered by the sensors and the resulting network is connected. Existing solutions allow individual sensor nodes to determine the sensing direction for maximum target coverage which produces sensing coverage redundancy and much overhead. Gathering nodes into clusters might provide a better solution to this problem. In this paper, we have designed distributed clustering and target coverage algorithms to address the problem in an energy-efficient way. To the best of our knowledge, this is the first work that exploits cluster heads to determine the active sensing nodes and their directions for solving target coverage problems in DSNs. Our extensive simulation study shows that our system outperforms a number of state-of-the-art approaches.
Highlights
A directional sensor network (DSN) is composed of a large number of directional sensor devices that send sensedevent reports to a sink
The first parameter of Eq 2 denotes how much fraction of the residual energy is remaining over the initial energy, the second parameter represents the density of the neighbor nodes, and the third parameter is corresponding to the distance of a sensor node from the sink
4.6.2 Weight factors Setting appropriate values for the weight factors w1, w2, w3, c1, and c2 is very important for achieving optimal solutions to clustering and coverage problems that we have addressed in this work
Summary
A directional sensor network (DSN) is composed of a large number of directional sensor devices that send sensedevent reports to a sink. None of them consider the importance of utilizing the cluster heads in minimizing the number of active sensing nodes and determining their directions to maximize the target coverage. In [28], the authors proposed an autonomous cluster algorithm (ACDA) for forming a cluster to achieve both connectivity and sufficient coverage with directional sensor networks This ACDA is a randomized distributed algorithm having four phases: phase I: determining the active sensing sectors, phase II: choosing the communication sectors and cluster heads, phase III: selecting the gateways, and phase IV: renewing the cluster head and gateway. We provide a better algorithm which will consider the residual energy of the sensor and distance from the sink to calculate the cluster head and gateway in directional sensor networks.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
