Ant-colony-based scheduling algorithm for energy-efficient coverage of WSN

Sensors in most wireless sensor networks (WSNs) work with batteries as their energy source, it is usually infeasible to recharge or replace batteries when they discharge. Thus, solving the efficient-energy coverage (EEC) problem is an important issue for a WSN. Therefore, it is necessary to schedule the activities of the devices in a WSN to save the network's limited energy and prolong its lifetime. In this paper, we propose an ant-colony-based acheduling algorithm (ACB-SA) to solve the EEC problem. Our algorithm is a simplified version of the conventional ant colony optimization algorithm, optimized for solving the EEC problem. We also use the probability sensor detection model and apply our proposed algorithm to a heterogeneous sensor set, which represents a more realistic approach to solving the EEC problem. Simulation results are performed to verify the effectiveness of the ACB-SA for solving the EEC problem in comparison with other algorithms.