Robust and Efficient Energy Harvested-Aware Routing Protocol with Clustering Approach in Body Area Networks

Zahid Ullah, Imran Ahmed, Tamleek Ali, Naveed Ahmad, Fahim Niaz, Yue Cao

Research output: Contribution to journalArticlepeer-review

53 Citations (Scopus)


Wireless body area network (WBAN) is one of the specialized branches of wireless sensor networks (WSNs), which draws attention from various fields of science, such as medicine, engineering, physics, biology, and computer science. It has emerged as an important research area contributing to sports, social welfare, and medical treatment. One of the most important technologies of WBANs is routing technology. For efficient routing in WBANs, multiple network operations, such as network stability, throughput, energy efficiency, end-to-end delay, and packet delivery ratio, must be considered. In this paper, a robust and efficient Energy Harvested-aware Routing protocol with Clustering approach in Body area networks (EH-RCB) is proposed. It is designed with the intent to stabilize the operation of WBANs by choosing the best forwarder node, which is based on optimal calculated Cost Function (C.F). The C.F considers the link SNR, required transmission power, the distance between nodes, and total available energy, i.e., harvested energy and residual energy. Comprehensive simulation has been conducted, supported by NS-2 and C++ simulations tools to compare EH-RCB with existing protocols named DSCB, EERP, RE-ATTEMPT, and EECBSR. The results indicate a significant improvement in the EH-RCB in terms of the end-to-end delay network stability, packet delivery ratio, and network throughput.

Original languageEnglish
Article number8664573
Pages (from-to)33906-33921
Number of pages16
JournalIEEE Access
Publication statusPublished - 2019
Externally publishedYes


  • Clustering
  • WBANs
  • end-to-end delay
  • harvesting
  • network stability
  • packet delivery ratio
  • throughput


Dive into the research topics of 'Robust and Efficient Energy Harvested-Aware Routing Protocol with Clustering Approach in Body Area Networks'. Together they form a unique fingerprint.

Cite this