Mobile Networks and Applications

, Volume 12, Issue 5–6, pp 381–391 | Cite as

Multi-hop Clustering Based on Neighborhood Benchmark in Mobile Ad-hoc Networks

  • Stephen S. Yau
  • Wei Gao


Large-scale mobile ad-hoc networks require flexible and stable clustered network structure for efficient data collection and dissemination. In this paper, a technique is presented to construct multi-hop clusters with balanced sizes, based on the neighborhood benchmark (NB) to quantify the connectivity and link stability of mobile nodes. By exploiting autonomous clusterhead selection and a specialized handshake process with the clusterheads, the nodes with highest NB scores are selected as clusterheads and all the clusters constructed are connected. The deviation of cluster sizes is kept small using a partial probability-based approach. Our technique generates highly stable multi-hop clusters with low overhead, and provides the flexibility of controlling the cluster radius adaptively for various network applications.


mobile ad-hoc networks multi-hop clusters neighborhood benchmark balanced sizes 



This work was supported by the National Science Foundation under grant number ITR-CYBERTRUST 0430565.


  1. 1.
    Amis AD, Prakash R, Huynh D, Vuong T (2000) Max-min d-cluster formation in wireless ad hoc networks. In: Proc. 19th annual joint conference of the IEEE computer and communications societies (INFOCOM). IEEE, Piscataway, pp 32–41Google Scholar
  2. 2.
    An B, Papavassiliou S (2001) A mobility-based clustering approach to support mobility management and multicast routing in mobile ad-hoc wireless networks. Int J Netw Manage 11(6):387–395CrossRefGoogle Scholar
  3. 3.
    Belding-Royer EM (2002) Hierarchical routing in ad-hoc mobile networks. Wirel Commun Mob Comput 2(5):515–532CrossRefGoogle Scholar
  4. 4.
    Chatterjee M, Das SK, Turgut D (2002) Wca: a weighted clustering algorithm for mobile ad hoc networks. J Clust Comput 5(2):193–204CrossRefGoogle Scholar
  5. 5.
    Chen Y-P, Liestman AL (2002) Approximating minimum size weakly-connected dominating sets for clustering mobile ad hoc networks. In: Proc. 3rd ACM interational symposium on mobile ad hoc networking and computing (MobiHoc). ACM, New York, pp 165–172CrossRefGoogle Scholar
  6. 6.
    Chiang C-C, Wu H-K, Liu W, Gerla M (1997) Routing in clustered multihop mobile wireless networks with fading channel. In: Proc. IEEE Singapore international conference on networks (SICON). IEEE, Piscataway, pp 197–211Google Scholar
  7. 7.
    Ephremides A, Wieselthier JE, Baker DJ (1987) A design concept for reliable mobile radio networks with frequency hopping signaling. Proc IEEE 75(1):56–73CrossRefGoogle Scholar
  8. 8.
    Kim D, Ha S, Choi Y (1998) k-hop cluster-based dynamic source routing in wireless ad-hoc packet radio networks. In: Proc. IEEE vehicular technology conference (VTC). IEEE, Piscataway, pp 224–228Google Scholar
  9. 9.
    McDonald A, Znati TF (1999) A mobility-based framework for adaptive clustering in wireless ad hoc networks. IEEE J Sel Areas Commun 17(8):1466–1487CrossRefGoogle Scholar
  10. 10.
    Nocetti FG, Gonzalez JS, Stojmenovic I (2003) Connectivity based k-hop clustering in wireless networks. Telecommun Syst 22(1–4):205–220CrossRefGoogle Scholar
  11. 11.
    Ramaswamy L, Gedik B, Liu L (2005) A distributed approach to node clustering in decentralized peer-to-peer networks. IEEE Trans Parallel Distrib Syst 16(9):814–829CrossRefGoogle Scholar
  12. 12.
    Ratnasamy S, Francis P, Handley M, Karp R, Schenker S (2001) A scalable content-addressable network. In: Proc. ACM SIGCOMM. ACM, New York, pp 161–172Google Scholar
  13. 13.
    Stoica I, Morris R, Karger D, Kaashoek F, Balakrishnan H (2001) Chord: a scalable peer-to-peer lookup service for internet applications. In: Proc. ACM SIGCOMM. ACM, New York, pp 149–160Google Scholar
  14. 14.
    Tsai JT, Gerla M (1995) Multicluster, mobile, multimedia radio network. J Wirel Netw 1(3):255–265CrossRefGoogle Scholar
  15. 15.
    Wu J, Li H (1999) On calculating connected dominating set for efficient routing in ad hoc wireless networks. In: Proc. 3rd Int’l workshop on discrete algorithms and methods for mobile computing and communications (DIAL-M), Seattle, 20 August 1999, pp 7–14Google Scholar
  16. 16.
    Wu J, Lou W (2003) Forward node set based broadcast in clustered mobile ad hoc networks. Wirel Commun Mob Comput 3(2):155–173CrossRefGoogle Scholar
  17. 17.
    Yu JY, Chong PHJ (2005) A survey of clustering schemes for mobile ad hoc networks. Commun Surv Tutor 7(1):32–48CrossRefGoogle Scholar
  18. 18.
    Zhao BY, Huang L, Stribling J, Rhea SC, Joseph AD, Kubiatowicz JD (2004) Tapestry: a resilient global-scale overlay for service deployment. IEEE J Sel Areas Commun 22(1):41–53CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringArizona State UniversityTempeUSA

Personalised recommendations