K-Coverage Model Based on Genetic Algorithm to Extend WSN Lifetime

Currently, wireless sensor networks (WSNs) are extensively used in target monitoring applications. Classical target coverage methods often assume that the environment is perfectly known, and each target is covered by only one sensor. Such algorithms, however, are inflexible, especially if a sensor died, i.e., ran out of energy, and hence, a target may need to be covered by more than one sensor, which is known as the K-coverage problem. The K-coverage problem is a time and energy consuming process, and the organization between sensors is required all the time. To address this problem, this article proposes a K-coverage model based on genetic algorithm to extend a WSN lifetime. In the search for the optimum active cover, different factors such as targets' positions, the expected consumed energy, and coverage range of each sensor are taken into account. A set of experiments were conducted using different K-coverage cases. Compared to some state-of-the-art methods, the proposed model improved the WSN's performance regarding to the amount of the consumed energy, the network lifetime, and the required time to switch between different covers.