1st International ICST Workshop on Technologies for Ambient Information Society

Research Article

A stable clustering algorithm for mobile ad hoc networks based on attractor selection

  • @INPROCEEDINGS{10.4108/ICST.BIONETICS2008.4736,
        author={Gen Nishikawa and Fukuhito Ooshita and Hirotsugu Kakugawa and Toshimitsu Masuzawa},
        title={A stable clustering algorithm for mobile ad hoc networks based on attractor selection},
        proceedings={1st International ICST Workshop on Technologies for Ambient Information Society},
        publisher={ACM},
        proceedings_a={TAIS},
        year={2010},
        month={5},
        keywords={Attractor selection Distributed algorithm Clustering Mobile ad hoc networks Stability},
        doi={10.4108/ICST.BIONETICS2008.4736}
    }
    
  • Gen Nishikawa
    Fukuhito Ooshita
    Hirotsugu Kakugawa
    Toshimitsu Masuzawa
    Year: 2010
    A stable clustering algorithm for mobile ad hoc networks based on attractor selection
    TAIS
    ICST
    DOI: 10.4108/ICST.BIONETICS2008.4736
Gen Nishikawa1,*, Fukuhito Ooshita1,*, Hirotsugu Kakugawa1,*, Toshimitsu Masuzawa1,*
  • 1: Graduate School of Information Science and Technology, Osaka University, 1-3 Machikaneyama, Toyonaka, Osaka, Japan.
*Contact email: g-nisikw@ist.osaka-u.ac.jp, f-oosita@ist.osaka-u.ac.jp, kakugawa@ist.osaka-u.ac.jp, masuzawa@ist.osaka-u.ac.jp

Abstract

With the spread of wireless technology, mobile ad hoc networks is getting increased attention in recent years. In mobile ad hoc networks, network topologies dynamically change because of node mobility. Thus, it is important to design an algorithm that has strong stability against frequent topology changes. Attractor selection is one of the biologically inspired approaches that have strong stability against environmental changes. In this paper, we propose a stable clustering algorithm based on attractor selection for mobile ad hoc networks. Clustering is a fundamental problem for distributed systems and makes it easy to manage large scale networks. We show the effectiveness of our algorithm by simulations.