Residual-Energy Aware Modeling and Analysis of Time-Varying Wireless Sensor Networks

Zhaoming Ding, Lianfeng Shen, Hongyang Chen, Feng Yan, Nirwan Ansari

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
JournalIEEE Communications Letters
StateAccepted/In press - 2021

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering


  • Analytical models
  • Energy consumption
  • Energy efficiency
  • Markov chain
  • Markov processes
  • network lifetime
  • node-residual energy
  • Relays
  • Routing
  • Signal to noise ratio
  • Wireless sensor networks
  • wireless sensor networks


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