Analytical Model of Deployment Methods for Application of Sensors in Non-hostile Environment

• Main Authors: Kaiwartya, O., Kumar, S., Abdullah, A. H.
• Format: Article
• Published: Springer New York LLC 2017
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/81144/; http://dx.doi.org/10.1007/s11277-017-4584-6

Wireless Sensor Networks (WSNs) has become one the promising research theme due to the availability of wide range of applications useful for almost each and every area of society. One fundamental application of WSNs is event detection in a Region of Interest (RoI). A set of sensors are deployed to monitor any events inside RoI. In such monitoring applications, both the quality of detection as well as resource requirement in terms of sensors must be optimized while satisfying a certain level of detection guaranty. Therefore, carrying out an optimal sensor deployment is a challenging task for achieving a certain coverage quality with minimum energy consumption and network cost. This paper proposes analytical models for critically analyzing the performance of different deployment techniques to provide insight on the design parameters and system behaviors. Mathematical formulations have been derived to measure the quality of coverage, energy consumption and network cost of geometrical deployment patterns in terms of different metrics; namely, size of RoI, number of sensors and their sensing range. The deployment patterns are modeled by using different shapes of mathematical geometry such square, tri-tilling-hexagon and hexagon. Simulations are carried out using MATLAB considering realistic parameter setting and results are comparatively analyzed for deployment techniques. Analysis of results attests the superiority of Tri Hexagon Tiling (THT) deployment in terms of 2-coverage, energy consumption and network cost to the square and hexagon deployments. In terms of 3-coverage and 4-coverage, hexagon deployment is better as compared to THT and square deployments.