Stability-based multi-objective clustering in mobile ad hoc networks

Hui Cheng, Jiannong Cao, Xingwei Wang, Sajal K. Das

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)

Abstract

In this paper, we propose a stability-based multi-objective clustering algorithm, which can achieve stable cluster structure by exploiting the node movement proximity, and meanwhile optimize multiple clustering metrics simultaneously by a reputable multi-objective evolutionary algorithm (MOEA). The performance of the proposed algorithm has been evaluated through extensive simulations with network topologies of various sizes. The results demonstrated that the clustered topologies generated by our algorithm have good performance in terms of stability. Our algorithm can achieve optimal cluster structure with respect to each clustering metric on small-scale network topology. For large-scale network topology, it also outperforms WCA, a well known multi-objective clustering algorithm using a weighted sum of multiple metrics.
Original languageEnglish
Title of host publicationACM International Conference Proceeding Series - Proceedings of the 3rd International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks
Volume191
DOIs
Publication statusPublished - 1 Dec 2006
Event3rd International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks - Waterloo, ON, Canada
Duration: 7 Aug 20068 Sep 2006

Conference

Conference3rd International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks
CountryCanada
CityWaterloo, ON
Period7/08/068/09/06

Keywords

  • Ad hoc networks
  • Clustering
  • Group mobility
  • Multi-objective evolutionary optimization

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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