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An Energy-Efficient WSN Routing Protocol Using Genetic Algorithms and Predictive Coding

  • Behzad Oveisi*
  • , Michel Kadoch
  • , Qia Li
  • , Tao Hong
  • *Corresponding author for this work
  • Université du Quebec
  • École de technologie supérieure
  • University of Electronic Science and Technology of China

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In order to achieve the most energy-efficient outcomes for wireless sensor networks (WSNs), this study suggests a unique energy-efficient routing protocol based on artificial inelegance approaches. The main goal of the project is to create a new routing protocol that will extend the lifetime of the network by reducing energy consumption through data compression and balanced energy usage. Next, utilizing the simulation tool in wireless sensor networks, the simulation is carried out for the suggested model. The network lifetime in the simulation scenarios is presented by the suggested model, which is assessed in the simulations based on the energy consumption of the network, the quantity of dead nodes, the throughput of the network, and the network’s delay versus the number of rounds in the network.

Original languageEnglish
Title of host publicationInformation Processing and Network Provisioning - 3rd International Conference, ICIPNP 2024, Proceedings
EditorsMichel Kadoch, Mohamed Cheriet, Xuesong Qiu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages1-14
Number of pages14
ISBN (Print)9789819664580
DOIs
StatePublished - 2025
Event3rd International Conference on Information Processing and Network Provisioning, ICIPNP 2024 - Beijing, China
Duration: 14 Jun 202416 Jun 2024

Publication series

NameCommunications in Computer and Information Science
Volume2419 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference3rd International Conference on Information Processing and Network Provisioning, ICIPNP 2024
Country/TerritoryChina
CityBeijing
Period14/06/2416/06/24

Keywords

  • Energy Efficiency
  • Genetic Algorithm
  • Predictive Coding
  • Routing Protocol
  • Wireless Sensor Networks

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