Jenga-Inspired Optimization Algorithm for Energy-Efficient Coverage of Unstructured WSNs

The Energy-Efficient Coverage (EEC) problem in unstructured Wireless Sensor Networks (WSNs) is an important issue because WSNs have limited energy. In this letter, we propose a novel stochastic optimization algorithm, called the Jenga-Inspired Optimization Algorithm (JOA), which overcomes some of the weaknesses of other optimization algorithms for solving the EEC problem. The JOA was inspired by Jenga which is a well-known board game. We also introduce the probabilistic sensor detection model, which leads to a more realistic approach to solving the EEC problem. Simulation results are conducted to verify the effectiveness of the JOA for solving the EEC problem in comparison with existing algorithms.