Genetic Algorithm-based Optimal Wireless Sensor Network Deployment

Many wireless sensor network (WSN) applications have achieved significant advances in sensor node technology. Sensor nodes are able to communicate and sense environmental conditions, however, deploying these nodes can be expensive and dangerous in some cases, which leads to random deployment as the only possible solution. The random deployment may lead to uncovered or unconnected areas, duplicated or missed data, and to waste more energy. Therefore, a Genetic Algorithm (GA) based methodology is implemented for self-organized WSN. In order to implement the process of WSN deployment and ensure low energy consumption, an optimization method is required. Based on the experimental results, GA helps in identifying the best position for each sensor node in order to meet network connectivity and coverage.