Skip to main content
Log in

A randomized clustering of anonymous wireless ad hoc networks with an application to the initialization problem

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

The Distributed Mobility-Adaptive Clustering (DMAC) due to Basagni partitions the nodes of a mobile ad hoc network into clusters, thus giving the network a hierarchical organization. This algorithm supports the mobility of the nodes, even during the cluster formation. The main feature of DMAC is that in a weighted network (in which two or more nodes cannot have the same weight), nodes have to choose the clusterheads taking into account only the node weight, i.e. the mobility when a node weight is the inverse of its speed. In our approach many nodes may have the same speed and hence the same weight. We assume that nodes have no identities and the number of nodes, say n, is the only known parameter of the network. After the randomized clustering, we show that the initialization problem can be solved in a multi-hop ad hoc wireless network of n stations in O(k 1/2log 1/2 k)+D b −1+O(log (max (P i )+log 2max (P i )) broadcast rounds with high probability, where k is the number of clusters, D b is the blocking diameter and max (P i ), 1≤ik, is the maximum number of nodes in a cluster. Thus the initialization protocol presented here uses less broadcast rounds than the one in Ravelemanana (IEEE Trans. Parallel Distributed Syst. 18(1):17–28 2007).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Awerbuch B (1985) Complexity of networks synchronization. J ACM 32(4):804–823

    Article  MATH  MathSciNet  Google Scholar 

  2. Baker D, Ephremides A (1981) The architectural organization of a mobile radio network via a distributed algorithm. In: IEEE transactions on communications COM-29, vol 11, pp 1694–1701

  3. Banerjee S, Khuller S (2001) A clustering scheme for hierarchical control in multi-hop wireless networks. In: Proceedings of the 20th IEEE infocom 2001, vol 2, pp 1028–1037

  4. Basagni S (1999) Distributed clustering for ad hoc networks. In: Proceedings of the 1999 international symposium on parallel architectures, algorithms, and networks (I-SPAN’ 99). IEEE Computer Society, pp 310–315

  5. Basagni S, Ghosh R (2005) Limiting the impact of mobility on ad hoc clustering. In: Proceedings of the second ACM inter. workshop on performance evaluation of wireless ad hoc, sensor, and ubiquitous networks (PE-WASUN’ 05). IEEE Computer Society, pp 197–204

  6. Chaterjee M, Das SK, Turgut D (2002) WCA: A weighted clustering algorithm for mobile ad hoc networks. Clust Comput 5:193–204

    Article  Google Scholar 

  7. Czumai A, Rytter W (2006) Broadcasting algorithms in radio networks with unknown topology. J Algorithms 60(2):115–143

    Article  MathSciNet  Google Scholar 

  8. Ephremides A (1983) Design concepts for a mobile-user radio network. Comput Electr Eng 10(3):127–135

    Article  Google Scholar 

  9. Feller W (1968) An introduction to probability theory and its applications. Wiley, New York

    MATH  Google Scholar 

  10. Gerla M, Lin C (1997) Adaptive clustering for mobile wireless networks. J Selected Areas Commun 15(7):1265–1275

    Article  Google Scholar 

  11. Gerla M, Tsa J (1995) Multicluster, mobile, multimedia radio network. Wirel Netw 1(3):255–265

    Article  Google Scholar 

  12. Lavault C, Zaks S (1989) Constructing spanning trees in anonymous networks. Proc ACM PODC’89. ACM Press, New York, pp. 319–328

    Google Scholar 

  13. McDonald AB, Znati TA (1999) A mobility-based framework for adaptive clustering in wireless ad hoc networks. IEEE J Selected Areas Commun Special Issue on Wireless Ad Hoc Networks 17(8): 1466–1487

    Google Scholar 

  14. Mellier R, Myoupo JF (2006) A weighted clustering algorithm for mobile ad hoc networks with non-unique weights, the second international conference on wireless and mobile communications (ICWMC 2006). Bucharest, Romania, July 29–31

  15. Myoupo JF, Ravelomanana V, Thimonier L (2003) Average casde analysis-based protocols to initialize packet radio networks. Wirel Commun Mobile Comput 3:539–548

    Article  Google Scholar 

  16. Nakano K, Olariu S (2000) Randomized initialization protocols for ad hoc networks. IEEE Trans Parallel Distr Syst 11:749–759

    Article  Google Scholar 

  17. Nocetti FG, Solango JS, Stojmenovic I (2003) Connectivity-based k-hop clustering in wireless networks. Telecommun Syst 22(1–4):205–220

    Article  Google Scholar 

  18. Raab M, Steger A (1998) Balls into bins: a simple and tight analysis. In: Randomized and approximation techniques in computer science (RANDOM’98). Lecture notes in computer science, vol 1518. Springer, Berlin, pp 159–170

    Chapter  Google Scholar 

  19. Ravelomanana V (2007) Optimal initialization and gossiping algorithms for random radio networks. IEEE Trans Parallel Distributed Syst 18(1):17–28

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jean Frédéric Myoupo.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Myoupo, J.F., Cheikhna, A.O. & Sow, I. A randomized clustering of anonymous wireless ad hoc networks with an application to the initialization problem. J Supercomput 52, 135–148 (2010). https://doi.org/10.1007/s11227-009-0274-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-009-0274-9

Keywords

Navigation