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A Mobility Aware Technique for Clustering on Mobile Ad-Hoc Networks

  • Charalampos Konstantopoulos
  • Damianos Gavalas
  • Grammati Pantziou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4308)

Abstract

Clustering for mobile ad-hoc networks (MANETs) has attracted the interest of many researchers as it offers enhanced scalability and performance improvement. The main challenge of the clustering algorithms is the formation of stable clusters despite the topological changes due to the host mobility. In this paper, we present a novel clustering algorithm, which first predicts the future host mobility and then uses this information to build a stable clustering structure over hosts that will probably exhibit low mobility in the future. In this way, long lifetime for the clustering structure is guaranteed, thereby eliminating the need for frequent reclustering. For predicting the future host mobility, we use provably good information theoretic techniques, which allow on-line learning of a reliable probabilistic model for future mobility.

Keywords

Cluster Head Transmission Range Mobile Host IEEE Wireless Communication Mobility Prediction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Gerla, M., Tsai, J.: Multicluster, Mobile, Multimedia Radio Network. ACM Baltzer Journal of Wireless Network 1(3), 255–265 (1995)CrossRefGoogle Scholar
  2. 2.
    McDonald, A., Znatti, T.: A Mobility-Based Framework for Adaptive Clustering in Wireless Ad Hoc Networks. IEEE Journal on Selected Areas in Communications 17, 1466–1487 (1999)CrossRefGoogle Scholar
  3. 3.
    Basu, P., Khan, N., Little, T.: A Mobility Based Metric for Clustering in Mobile Ad Hoc Networks. In: Proc. of the 21st International Conference on Distributed Computing Systems Workshops (ICDCSW 2001), pp. 413–418 (2001)Google Scholar
  4. 4.
    Er, I., Seah, W.: Mobility-based d-Hop Clustering Algorithm for Mobile Ad Hoc Networks. In: Proc. of IEEE Wireless Communications and Networking Conference (WCNC 2004), vol. 4, pp. 2359–2364 (2004)Google Scholar
  5. 5.
    Basagni, S.: Distributed Clustering for Ad-Hoc Networks. In: Proc. of the 1999 International Symposium on Parallel Architectures, Algorithms and Networks (ISPAN 1999), pp. 310–315 (June 1999)Google Scholar
  6. 6.
    Basagni, S.: Distributed and Mobility-Adaptive Clustering for Multimedia Support in Multi-hop Wireless Networks. In: Proc. of IEEE International Vehicular Technology Conference, pp. 889–893 (September 1999)Google Scholar
  7. 7.
    Chatterjee, M., Das, S., Turgut, D.: WCA: A Weighted Clustering Algorithm for Mobile Ad Hoc Networks. Cluster Computing 5, 193–204 (2002)CrossRefGoogle Scholar
  8. 8.
    Sivavakeesar, S., Pavlou, G., Liotta, A.: Stable Clustering Through Mobility Prediction for Large-Scale Multihop Ad Hoc Networks. In: Proc. of the IEEE Wireless Communications and Networking Conference, WCNC 2004 (March 2004)Google Scholar
  9. 9.
    Johnson, D., Maltz, D.: Dynamic Source Routing in Ad Hoc Wireless Networks. In: Imelinsky, T., Korth, H. (eds.) Mobile Computing, pp. 153–181. Kluwer Academic Publishers, Dordrecht (1996)CrossRefGoogle Scholar
  10. 10.
    Bhattacharya, A., Das, S.K.: LeZi-Update: An Information-Theoretic Framework for Personal Mobility Tracking in PCS Networks. Wireless Networks 8, 121–135 (2002)MATHCrossRefGoogle Scholar
  11. 11.
    Bell, T.C., Cleary, J.G., Witten, I.H.: Text Compression. Prentice Hall, Englewood Cliffs (1990)Google Scholar
  12. 12.
    Ziv, J., Lempel, A.: Compression of Individual Sequences via Variable-rate Coding. IEEE Transactions on Information Theory 24(5), 530–536 (1978)MATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    Gerla, M., Kwon, T.J., Pei, G.: On Demand Routing in Large Ad Hoc Wireless Networks with Passive Clustering. In: Proc. of IEEE Wireless Communications and Networking Conference, WCNC 2000 (September 2000)Google Scholar
  14. 14.
    Marathe, V., Breu, H., Hunt III, H.B., Ravi, S.S., Rosenkrantz, D.J.: Simple Heuristics for Unit Disk Graphs. Networks 25(2), 59–68 (1995)MATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Charalampos Konstantopoulos
    • 1
  • Damianos Gavalas
    • 2
  • Grammati Pantziou
    • 3
  1. 1.Research Academic Computer Technology Institute andUniversity of PatrasGreece
  2. 2.Department of Cultural Technology and CommunicationUniversity of the AegeanGreece
  3. 3.Department of InformaticsTechnological Education Institution of AthensGreece

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