A LA Algorithm for solving the target coverage problemin wireless sensor networks

In order to find a solution for the target coverage problem in directional sensornetworks (WSNs), some researchers have recently introduced several efficient algorithms.These sensors are conventionally supposed to have a single power level and asingle coverage is just needed for targets. In other words, there are various sensingranges and power consumptions for these sensors under real conditions and at least ktimes monitoring is required for each target. The present paper ad- dresses this issue asthe target k-coverage with adjustable sensing range, which has not been already studied inWSNs. To solve this problem, two learning automata- based algorithms (Algorithms ۱and ۲) are proposed and equipped with a strong pruning rule that facilitates the selectionof appropriate sensor directions capa- ble of providing the targets with k-coverage.After evaluating the efficiency of the algorithms’ performance by conducting severalexperiments, the results were compared to those ones obtained by a greedy-basedalgorithm, which is discussed in the literature. Finding indicated that algorithms havesuperiority over their ri- vals regarding the prolonged lifetime of their network.

کلیدواژه ها:

Directional sensor networks ، Cover set formation ، Scheduling algorithms ، Learning automata ، k-coverage