Multilevel (k) Coverage Based on Probabilistic Sensing Model in Wireless Sensor Networks

• Main Authors: Chen, Yu-Ning, 陳佑寧
• Other Authors: Chen, Chiuyuan
• Format: Others
• Language: en_US
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/98fx73

碩士 === 國立交通大學 === 應用數學系所 === 107 === In this thesis, we consider multilevel (k) coverage in wireless sensor networks (WSNs) under a more realistic sensing model, called the probabilistic sensing model, in which the detection probability of a sensor decays as the distance between the target and the sensor increases. We propose a sensor deployment scheme called k-layer coverage scheme, which partitions the sensors into k subsets, each being regarded as forming one layer of coverage, and ensures that the detection probability contributed by “each layer” is not smaller than a predefined threshold pth, where 0 < pth < 1. Our k-layer coverage scheme uses a zone 1 & zone 1–2 strategy, in which zone 1 & zone 2 are a sensor’s sensing regions that have the highest and the second highest detection probability, respectively (zone 1–2 is the union of zone 1 & zone 2). By using such a zone 1 & zone 1–2 strategy, our k-layer coverage scheme guarantees a good multilevel (k) coverage quality. We propose an extremely efficient algorithm to calculate the radius r1 of zone 1. Since we always choose the radius r2 of zone 1–2 to be √ 3r1, our k-layer coverage scheme can be implemented quite efficiently. Experimental results also show that our k-layer coverage scheme indeed uses less sensors.