In this letter, the residual-energy aware feature of a sensor node in time-varying wireless sensor networks (WSNs) is analyzed and modeled as a Markov chain, upon which the state-transition probability (STP) about the energy level of any node with undetermined and deterministic residual energy can be evaluated. Based on Markov chain and energy-efficient relay search region models, an energy-efficient routing algorithm is proposed to further analyze the impact of STP with known residual energy on extending network lifetime of time-varying WSNs. Simulation results show that the proposed algorithm can effectively extend network lifetime even more than twice while holding a better energy efficiency as compared with the algorithm without considering node-residual energy changes.

中文翻译：

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时变无线传感器网络的剩余能量感知建模与分析

在这封信中，时变无线传感器网络 (WSN) 中传感器节点的剩余能量感知特征被分析并建模为马尔可夫链，基于该马尔可夫链，关于任何节点能量水平的状态转移概率 (STP)可以评估不确定和确定的剩余能量。基于马尔可夫链和节能中继搜索区域模型，提出了一种节能路由算法，以进一步分析已知剩余能量的STP对时变WSN网络寿命延长的影响。仿真结果表明，与不考虑节点剩余能量变化的算法相比，该算法可以有效地延长网络寿命甚至两倍以上，同时保持更好的能量效率。