Timely reliability modeling and evaluation of wireless sensor networks with adaptive N-policy sleep scheduling

• Published in: Reliability engineering & system safety Vol. 235; p. 109270
• Main Authors: Zhang, Changzhen, Yang, Jun, Wang, Ning
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2023
• Subjects: Adaptive N-policy sleep scheduling; Queueing model; Timely reliability; Wireless sensor networks; Wireless sensor networks; Queueing model; Timely reliability; Adaptive N-policy sleep scheduling
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2023.109270

•We propose an adaptive N-policy sleep scheduling for the high packet delay of WSNs.•A N-policy M/M/1/C queueing model with waiting time is established for sensor nodes.•We propose a timely reliability evaluation method for heterogeneous WSNs.•The proposed methods are verified by numerical experiments and a real case study. As an energy-efficient strategy, node sleep scheduling has become a hot topic of the energy conservation in wireless sensor networks (WSNs). Among these strategies, the N-policy sleep scheduling considers the energy consumption of node switching, thus effectively reducing the total energy consumption. However, node sleep will also increase the transmission packet delay, which cannot meet the timely reliability requirements of the network. To deal with this problem, we propose an adaptive N-policy sleep scheduling for sensor nodes. Next, in order to analyze the energy consumption and the packet delay under the proposed sleep scheduling, we establish the N-policy M/M/1/C queueing model with waiting time for heterogeneous sensor nodes, then derive the steady-state probability and obtain the performance metrics. Based on this, we establish the energy consumption model of sensor nodes and the delay model of packets. Besides, we propose a timely reliability evaluation model for heterogeneous WSNs, and the timely reliability is estimated by using the Monte Carlo simulation method. Finally, numerical experiments and a real case are performed to demonstrate the proposed sleep scheduling outperforms the N-policy sleep scheduling on delay, energy, and timely reliability.