HC-LEACH: Huffman Coding-based energy-efficient LEACH protocol for WSN

Djamila Mechta, Saad Harous

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Data aggregation is an energy-saving technology in wireless sensor networks (WSNs). Because of the high density of nodes in sensor networks, many nodes discover the same data (in many cases with a large quantity), leading to a lot of energy consumption and may be packets loss. These challenges can be resolved by using a data collection policy when routing packets from the source nodes to the base station (BS). Researchers are still struggling to choose an effective and appropriate data collection method from the current WSN literature. In this paper, we propose an energy-aware Huffman coding-based LEACH protocol for WSN (HC-LEACH). The experiment results show the effectiveness of the proposed scheme in enhancing energy consumption by approximately 38% compared to LEACH.

Original languageEnglish
Title of host publication2020 11th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2020
EditorsRajashree Paul
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages932-938
Number of pages7
ISBN (Electronic)9781728196565
DOIs
Publication statusPublished - Oct 28 2020
Event11th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2020 - Virtual, New York City, United States
Duration: Oct 28 2020Oct 31 2020

Publication series

Name2020 11th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2020

Conference

Conference11th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2020
Country/TerritoryUnited States
CityVirtual, New York City
Period10/28/2010/31/20

Keywords

  • Aggregation
  • Data compression
  • Network lifetime
  • Optimization
  • WSN

ASJC Scopus subject areas

  • Computer Science Applications
  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Computer Networks and Communications

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