Wireless sensor networks (WSNs) generally consist of densely deployed sensor nodes that depend on batteries for energy. Having a large number of densely deployed sensor nodes causes energy waste and high redundancy in sensor data transmissions. The problems of power limitation and high redundancy in sensing coverage can be solved by appropriate scheduling of node activity among sensor nodes. In this paper, we propose a cellular automata based node scheduling algorithm for prolonging network lifetime with a balance of energy savings among nodes while achieving high coverage quality. Based on a cellular automata framework, we propose a new mathematical model for the node scheduling algorithm. The proposed algorithm uses local interaction based on environmental state signaling for making scheduling decisions. We analyze the system behavior and derive steady states of the proposed system. Simulation results show that the proposed algorithm outperforms existing protocols by providing energy balance with significant energy savings while maintaining sensing coverage quality.

Wireless sensor networks (WSNs)

This paper proposes a control-based approach for duty cycle adaptation in wireless sensor networks. The proposed method, QCon, controls duty cycle through queue management in order to achieve high performance under variable traffic rates. To minimize energy consumption while meeting delay requirement, we design a feedback controller, which adapts the sleeping time according to dynamically changing traffic by constraining the queue length at a predetermined value. Based on control theory, we analyze the adaptive behavior of QCon and derive conditions for system stability. Results from asymptotic analysis and simulations indicate that QCon outperforms existing scheduling protocol by achieving more energy savings while satisfying delay requirement.