A comparative study on performances of sensor deployment algorithms in WSN

Deployment of mobile sensors to achieve full coverage of a region of interest and connectivity within sensors are the most significant and practically challenging issues for increasing lifetime of a wireless sensor network (WSN). Extensive researches have been carried out in recent past to address these issues and many deployment algorithms have been developed. However, for a decision maker it is very important to adopt an objective-specific suitable algorithm for deployment of sensors to address various practical aspects in real time. In this paper, we present a comparative study on performances of three well-developed deployment algorithms such as grid-based self-deployment and algorithms utilizing optimization techniques such as particle swarm and genetic algorithm. Performances of these three deployment schemes are evaluated in terms of coverage, uniformity, connectivity, and computational time in absence of any obstacles as well as in presence of randomly placed few unknown obstacles in an area of interest. The effect of initial positions of sensors on the performances of these three algorithms is also investigated. To achieve this objective, a series of simulation experiments are conducted and results are presented in this paper.