Ant-Colony-Based Scheduling Algorithm for Energy-Efficient Coverage of WSN

• Published in: IEEE sensors journal Vol. 12; no. 10; pp. 3036 - 3046
• Main Authors: Lee, Joon-Woo, Lee, Ju-Jang
• Format: Journal Article
• Language: English
• Published: IEEE 01.10.2012
• Subjects: Ant colony optimization; Ant colony optimization (ACO); ant-colony-based scheduling algorithm (ACB-SA); Energy efficiency; energy-efficient coverage (EEC); heterogeneous sensor set; Scheduling algorithms; Sensor phenomena and characterization; wireless sensor network (WSN); Wireless sensor networks
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2012.2208742

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.