A Multi-Layer Cluster Based Energy Efficient Routing Scheme for UWSNs

Wahab Khan*, Hua Wang, Muhammad Shahid Anwar, Muhammad Ayaz, Sadique Ahmad, Inam Ullah

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

68 Citations (Scopus)

Abstract

Underwater Wireless Sensor Networks (UWSNs) have emerged as a remarkable interest for scholars worldwide in terms of various applications such as monitoring offshore oil and gas reservoirs, pollution, oceans for defense, and other applications such as tsunami. Terrestrial Wireless Sensor Networks (TWSN) and UWSNs share many characteristics apart from having different communication medium and working environment as UWSNs face the challenges of low-bandwidth, long latency, and high bit error rate. These have caused for UWSNs many problems such as low reliability, packet retransmission, and high consumption of energy. To alleviate the aforementioned issues, many techniques have been proposed. However, most of them merely consider the issue of hotspot which occurs due to the unbalanced transmission of load on sensor nodes near the surface sink. In this article, we propose a multi-layer cluster-based Energy Efficient (MLCEE) protocol for UWSNs to address the issue of hotspot and energy consumption. There are different stages in MLCEE, first of which is the division of the whole network in layers, the second is clustering of the nodes at same layers. In the last stage of transmission, the cluster head (CH) selects the next hop among the CHs based on greater fitness value, small Hopid and small layer number. To mitigate the issue of hotspot, the first layer remains un-clustered and any node in the first layer transfers data to the sink directly while cluster heads (CHs) are selected based on Bayesian Probability and residual energy. The simulation results of the proposed technique, done using MATLAB, have revealed that MLCEE achieves superior performance than the other techniques with regard to the network lifetime, energy consumption, and data transmission amount.

Original languageEnglish
Article number8734057
Pages (from-to)77398-77410
Number of pages13
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 2019

Keywords

  • BN Bayesian probability (BN)
  • Underwater wireless sensor networks (UWSNs)
  • cluster head (CH) selection
  • dynamic clustering
  • energy efficiency
  • network lifetime

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