Target coverage heuristic based on learning automata in wireless sensor networks

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In wireless sensors networks, the sensor nodes are densely deployed. Owing to this excessive deployment of sensor nodes, each target is covered by multiple sensors at a time. To prolong the network lifetime, the authors can schedule the sensor activity in such a way that only a subset of sensor nodes, called cover set, is sufficient enough to cover all the targets. In this study, they propose an energy-efficient scheduling algorithm based on learning automata for target coverage problem. The learning automata-based technique helps a sensor node to select its appropriate state (either active or sleep ). To prove the effectiveness of their proposed scheduling method, they conduct a detailed set of simulations and compare the performance of their algorithm with the existing algorithms.