LBSNN: Neural Networks-based Moving Sink

Djamila Mechta, Saad Harous

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

3 Citations (Scopus)

Abstract

In this paper, we focus on Neural Networks (NN) to be applied for moving sink in Wireless Sensor Networks (WSNs). The system under consideration is composed of a set of a large number of autonomous nodes equipped with limited batteries not rechargeable. Energy consumption has always been a problem for this kind of network, the mobility of the base station (BS) has been exploited in huge projects to solve this problem and extend the lifetime of WSN. There are a number of different models of swarm intelligence that can provide powerful inspiration for researchers in the WSN mobile domain, such as ant colonization optimization (ACO), optimization of swarms (AFSA), bacterial forage and others. The main objective of our work is to propose a new mobility scheme of BS based on neural networks. We have implemented our proposed protocol LBSNN and compared the results obtained with the LEACH protocol and found satisfactory results. Experiments demonstrate the efficiency of LBSNN is meaningfully better and that our proposed model leads to a clear increase in network lifetime.

Original languageEnglish
Title of host publication2018 9th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2018
EditorsSatyajit Chakrabarti, Himadri Nath Saha
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages475-481
Number of pages7
ISBN (Electronic)9781538676936
DOIs
Publication statusPublished - Nov 2018
Event9th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2018 - New York City, United States
Duration: Nov 8 2018Nov 10 2018

Publication series

Name2018 9th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2018

Conference

Conference9th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2018
Country/TerritoryUnited States
CityNew York City
Period11/8/1811/10/18

Keywords

  • Bio-inspired Methods
  • Mobile BS
  • Neural Networks.
  • Optimization
  • WSNs

ASJC Scopus subject areas

  • Instrumentation
  • Computer Networks and Communications
  • Computer Science Applications
  • Electrical and Electronic Engineering

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