I. Introduction
In today's world, WSN have become a promising technology to cater to successful implementation of diverse applications ranging from environmental monitoring to mission critical ones. WSN is made up of a many low powered sensor nodes that are spatially distributed in a network. These sensor nodes operate in an autonomous manner and have limited communication, computation and sensing capabilities [1]. A number of investigations related to QoS parameters of paramount importance like energy efficiency, reliability and latency exist in literature. These researches assume that a sufficiently large number of sensor nodes are deployed. Instead, as a starting point in any WSN design, there is a need to compute the optimum density of sensor nodes to be deployed in the network area such that these sensor nodes collectively can satisfy temporal and spatial coverage requirement, or alternatively provide maximum sensing coverage in a given economical constraint. Deployment of an insufficient number of sensor nodes may lead to failure of the very purpose of the application, whereas over deployment will lead to higher system cost.