Enhanced Message-Passing Based LEACH Protocol for Wireless Sensor Networks

Jaeyoung Kang, Illsoo Sohn, Sang Hyun Lee

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This paper proposes a distributed energy-efficient clustering protocol for wireless sensor networks (WSNs). Based on low-energy adaptive clustering hierarchy (LEACH) protocol, the proposed LEACH-eXtended Message-Passing (LEACH-XMP) substantially improves a cluster formation algorithm, which is critical for WSN operations. Unlike the previous approaches, a realistic non-linear energy consumption model is considered, which renders the clustering optimization highly nonlinear and challenging. To this end, a state-of-the-art message-passing approach is introduced to develop an efficient distributed algorithm. The main benefits of the proposed technique are its inherent nature of a distributed algorithm and the saving of computational load imposed for each node. Thus, it proves useful for a practical deployment. In addition, the proposed algorithm rapidly converges to a very accurate solution within a few iterations. Simulation results ensure that the proposed LEACH-XMP maximizes the network lifetime and outperforms existing techniques consistently.

Original languageEnglish
JournalSensors (Basel, Switzerland)
Volume19
Issue number1
DOIs
Publication statusPublished - 2018 Dec 25

Fingerprint

Message passing
messages
Parallel algorithms
hierarchies
Cluster Analysis
Wireless sensor networks
Network protocols
sensors
Energy utilization
energy
energy consumption
iteration
life (durability)
optimization
simulation
xanthosine monophosphate

Keywords

  • LEACH
  • message passing
  • nonlinear power consumption

ASJC Scopus subject areas

  • Analytical Chemistry
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

Cite this

Enhanced Message-Passing Based LEACH Protocol for Wireless Sensor Networks. / Kang, Jaeyoung; Sohn, Illsoo; Lee, Sang Hyun.

In: Sensors (Basel, Switzerland), Vol. 19, No. 1, 25.12.2018.

Research output: Contribution to journalArticle

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