Resilience Enhancement Optimization for Wireless Sensor Networks Considering the Transmission Reliability

Reliable data packet transmission is essential for the Internet of Things. In dynamic and complex transmission environments, guaranteeing transmission reliability and enhancing network resilience is now a key research area in wireless sensor networks (WSNs). Current resilience enhancement strategies typically address survivability analysis (e.g., critical node identification) and recovery reconstruction optimization. However, existing studies on critical node identification are primarily focused on network topology, overlooking the reliable transmission mechanism. Besides, resilience optimization studies frequently fail to incorporate transmission reliability as a critical metric. To solve the above problems, this study develops a novel framework for resilience optimization of WSNs. First, a TOPSIS-based algorithm for identifying critical nodes is proposed, which emphasizes the impacts of environmental stochasticity and node failures on data transmission. On this basis, a transmission power optimization model considering the transmission reliability is constructed under the worst-case scenario, which maximizes the overall network lifetime. Furthermore, an algorithm for determining the recovery capacity limits of networks is constructed from internal reconfiguration, which can identify the critical time window for external intervention. Finally, a numerical case study on a military internet scenario was carried out to demonstrate the effectiveness of our proposed method.