Detection of Sensor Node-less Area Using A Genetic Algorithm for Wireless Sensor Network

The sensor networks, or more completely referred to as wireless sensor networks (WSNs), do not need a predetermined positioning in most cases. The sensor nodes (SNs) are randomly deployed in the SN's field, making a network. The deployment of the sensor nodes in the WSN depends on such an application, coverage area, and connectivity. The WSNs can deploy the SNs over a field with planning or deterministic topology, and self-organizing topologies. In the self-organizing topology, the SN's positions are formed randomly while the routes are unreliable and random. Because the random properties have many issues, it makes the SN's deployment becoming an essential issue. This paper aims to detect the most extensive area not covered by the sensor nodes in the WSN using a genetic algorithm (GA). Machine learning implementation has made a big through in widely computation use. The GA method could detect the sensor node-less area in the performance of the WSN with an accuracy of 91.67%.