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RaWMS - Random Walk Based Lightweight Membership Service for Wireless Ad Hoc Networks

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Abstract

This article presents RaWMS, a novel lightweight random membership service for ad hoc networks. The service provides each node with a partial uniformly chosen view of network nodes. Such a membership service is useful, for example, in data dissemination algorithms, lookup and discovery services, peer sampling services, and complete membership construction. The design of RaWMS is based on a novel reverse random walk (RW) sampling technique. The article includes a formal analysis of both the reverse RW sampling technique and RaWMS and verifies it through a detailed simulation study. In addition, RaWMS is compared both analytically and by simulations with a number of other known methods such as flooding and gossip-based techniques.

References

  1. Allavena, A., Demers, A., and Hopcroft, J. E. 2005. Correctness of a gossip based membership protocol. In Proceedings of the 24th Annual ACM Symposium on Principles of Distributed Computing (PODC). ACM, New York, 292--301. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Avin, C. and Ercal, G. 2005. Bounds on the mixing time and partial cover of ad-hoc and sensor networks. In Proceedings of the 2nd European Workshop on Wireless Sensor Networks (EWSN).Google ScholarGoogle Scholar
  3. Bar-Yossef, Z., Berg, A., Chien, S., Fakcharoenphol, J., and Weitz, D. 2000. Approximating aggregate queries about Web pages via random walks. In Proceedings of the 26th International Conference on Very Large Data Bases (VLDB). ACM, New York, 535--544. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Barr, R., Haas, Z. J., and van Renesse, R. JiST/SWANS Java in simulation time/ scalable wireless ad hoc network simulator. Available at http://jist.ece.cornell.edu/, Cornell University.Google ScholarGoogle Scholar
  5. Birman, K. P., Hayden, M., Ozkasap, O., Xiao, Z., Budiu, M., and Minsky, Y. 1999. Bimodal multicast. ACM Trans. Comput. Syst. 17, 2, 41--88. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Bollobas, B. 2001. Random Graphs, 2nd ed. Cambridge University Press, Cambridge, MA.Google ScholarGoogle Scholar
  7. Boyd, S., Diaconis, P., and Xiao, L. 2004. Fastest mixing Markov chain on a graph. SIAM Rev. 46, 4, 667--689. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Boyd, S., Ghosh, A., Prabhakar, B., and Shah, D. 2005. Mixing times for random walks on geometric random graphs. In Proceedings of the 2nd SIAM Workshop on Analytic Algorithmics and Combinatorics (ANALCO). SIAM, Philadelphia, PA.Google ScholarGoogle Scholar
  9. Chandra, R., Ramasubramanian, V., and Birman, K. 2001. Anonymous gossip: Improving multicast reliability in mobile ad-hoc networks. In Proceedings of the 21st International Conference on Distributed Computing Systems (ICDCS). 275. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Chaum, D. L. 1981. Untraceable electronic mail, return addresses, and digital pseudonyms. Commun. ACM 24, 2, 84--90. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Chernoff, H. 1952. A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations. American Mathematical Society 23, 493--507.Google ScholarGoogle Scholar
  12. Chockler, G., Keidar, I., and Vitenberg, R. 2001. Group communication specifications: a comprehensive study. ACM Comput. Surv. 33, 4, 427--469. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Diaconis, P. and Stroock, D. 1991. Geometric bounds for eigenvalues of Markov chains. Ann. Appl. Probab. 1, 36--61.Google ScholarGoogle ScholarCross RefCross Ref
  14. Dolev, S., Schiller, E., and Welch, J. 2002. Random walk for self-stabilizing group communication in ad hoc networks. In Proceedings of the 21st Annual Symposium on Principles of Distributed Computing (PODC). ACM, New York, 259--259. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Erdös, P. and Renyi, A. 1960. On the evolution of random graphs. Publ. Math. Inst. Hungar. Acad. Sci. 5, 17--61.Google ScholarGoogle Scholar
  16. Eugster, P. T., Guerraoui, R., Handurukande, S. B., Kouznetsov, P., and Kermar rec, A.-M. 2003. Lightweight probabilistic broadcast. ACM Trans. Comput. Syst. (TOCS) 21, 4, 341--374. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Feige, U. 1996. A fast randomized LOGSPACE algorithm for graph connectivity. Theoret. Comput. Sci. 169, 2, 147--160. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Fenner, T. I. and Frieze, A. M. 1982. On the connectivity of random m-orientable graphs and digraphs. Combinatorica 2, 347--359.Google ScholarGoogle ScholarCross RefCross Ref
  19. Ferro, E. and Potorti, F. 2005. Bluetooth and wi-fi wireless protocols: A survey and a comparison. IEEE Wireless Communications 12, 12 -- 26. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Freedman, M. J. and Morris, R. 2002. Tarzan: A peer-to-peer anonymizing network layer. In Proceedings of the 9th ACM Cconference on Computer and Communications Security (CCS). ACM, New York, 193--206. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Ganesh, A. J., Kermarrec, A.-M., and Massoulie, L. 2001. SCAMP: Peer-to-peer lightweight membership service for large-scale group communication. In Networked Group Communication. 44--55. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Gavidia, D., Voulgaris, S., and van Steen, M. 2005. Epidemic-style monitoring in large-scale sensor networks. Tech. Rep. IR-CS-012, Vrije Universiteit, Amsterdam, Netherlands. March.Google ScholarGoogle Scholar
  23. Gkantsidis, C., Mihail, M., and Saberi, A. 2004. Random walks in peer-to-peer networks. In Proceedings of the 23rd Conference of the IEEE Communications Society (INFOCOM). IEEE Computer Society Press, Los Alamitos, CA, 259--259.Google ScholarGoogle Scholar
  24. Gupta, P. and Kumar, P. 1998. Critical power for asymptotic connectivity in wireless networks. In Stochastic Analysis, Control, Optimization and Applications. 547--566.Google ScholarGoogle Scholar
  25. Guruswami, V. 2000. Rapidly mixing Markov chains: A comparison of techniques. Available at http://www.cs.washington.edu/homes/venkat/pubs/pubs.html.Google ScholarGoogle Scholar
  26. Haas, Z., Halpern, J., and Li, L. 2002. Gossip-based ad hoc routing. In Proceedings of the 21st Conference of the IEEE Communications Society (INFOCOM). IEEE Computer Society Press, Los Alamitos, CA, 1707--1716.Google ScholarGoogle Scholar
  27. Haas, Z. and Liang, B. 1999. Ad hoc mobility management with randomized database groups. In Proceedings of IEEE International Conference on Communications (ICC). IEEE Computer Society Press, Los Alamitos, CA, vol. 3. 1756 -- 1762.Google ScholarGoogle Scholar
  28. Horn, R. and Johnson, C. 1985. Matrix Analysis. Cambridge University Press.Google ScholarGoogle Scholar
  29. IEEE-802.11-Standard. Wireless LAN Media Access Control (MAC) and Physical Layer (PHY) Specifications. Downloadable at http://standards.ieee.org/getieee802/.Google ScholarGoogle Scholar
  30. Jelasity, M. and Babaoglu, O. 2005. T-Man: Gossip-based overlay topology management. In Proceedings of the 3rd International Workshop on Engineering Self-Organising Systems (ESOA). Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Jelasity, M. and van Steen, M. 2002. Large-scale newscast computing on the internet. Tech. Rep. IR-503, Vrije Universiteit, Amsterdam, Netherlands. October.Google ScholarGoogle Scholar
  32. Jelasity, M., Voulgaris, S., Guerraoui, R., Kermarrec, A.-M., and van Steen, M. 2007. Gossip-based peer sampling. ACM Trans. Comput. Syst. 25, 3, 8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Johnson, D. and Maltz, D. 1996. Dynamic source routing in ad hoc wireless networks. Mobile Comput. 353.Google ScholarGoogle Scholar
  34. Kermarrec, A.-M., Massoulie, L., and Ganesh, A. J. 2003. Probabilistic reliable dissemination in large-scale systems. IEEE Trans. Parall. Distrib. Syst. 14, 3 (Mar.), 248--258. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Kleinberg, J. 2000. The small-world phenomenon: An algorithmic perspective. In Proceedings of the 32nd ACM Symposium on Theory of Computing (STOC). ACM, New York, 163--170. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Lovász, L. 1993. Random walks on graphs: A survey. Combinatorics 2, 1--46.Google ScholarGoogle Scholar
  37. Luo, J., Eugster, P., and Hubaux, J.-P. 2003. Route driven gossip: Probabilistic reliable multicast in ad hoc networks. In Proceedings of the 23rd Conference of the IEEE Communications Society (INFOCOM). IEEE Computer Society Press, Los Alamitos, CA.Google ScholarGoogle Scholar
  38. Lv, C., Cao, P., Cohen, E., Li, K., and Shenker, S. 2002. Search and Replication in Unstructured Peer-to-Peer Networks. In Proceedings of the 16th International Conference on Supercomputing (ICS). 84--95. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Manku, G., Bawa, M., and Raghavan, P. 2003. Symphony: Distributed hashing in a small world. In Proceedings of the 4th USENIX Symposium on Internet Technologies and Systems (USITS). Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Massoulie, L., Merrer, E. L., Kermarrec, A.-M., and Ganesh, A. J. 2006. Peer counting and sampling in overlay networks: Random walk methods. In Proceedings of the 25th ACM Symposium on Principles of Distributed Computing (PODC). ACM, New York, 123--132. Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. Melamed, R. and Keidar, I. 2004. Araneola: A scalable reliable multicast system for dynamic environments. In 3rd IEEE International Symposium on Network Computing and Applications, (IEEE NCA). 5--14. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. Merrer, E. L., Kermarrec, A.-M., and Massoulie, L. 2006. Peer to peer size estimation in large and dynamic networks: A comparative study. In Proceedings of the 15th IEEE International Symposium on High Performance Distributed Computing (HPDC). IEEE Computer Society Press, Los Alamitos, CA, 7--17.Google ScholarGoogle Scholar
  43. Motwani, R. and Raghavan, P. 1995. Randomized Algorithms. Cambridge University Press, Cambridge, MA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Panchapakesan, P. and Manjunath, D. 2001. On the transmission range in dense ad hoc radio networks. In Proceedings of IEEE Signal Processing Communication (SPCOM). IEEE Computer Society Press, Los Alamitos, CA,Google ScholarGoogle Scholar
  45. Penrose, M. D. 2003. Random Geometric Graphs. Oxford University Press.Google ScholarGoogle Scholar
  46. Pucha, H., Das, S., and Hu, Y. C. 2004. Ekta: An efficient DHT substrate for distributed applications in mobile ad hoc networks. In Proceedings of the 6th IEEE Workshop on Mobile Computing Systems and Applications (WMCSA). IEEE Computer Society Press, Los Alamitos, CA, 163--173. Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. Reiter, M. K. and Rubin, A. D. 1999. Anonymous Web transactions with crowds. Commun. ACM 42, 2, 32--48. Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. Servetto, S. and Barrenechea, G. 2002. Constrained random walks on random graphs: Routing algorithms for large scale wireless sensor networks. In Proceedings of the 1st ACM International Workshop on Wireless Sensor Networks and Applications (WSNA). ACM, New York. Google ScholarGoogle ScholarDigital LibraryDigital Library
  49. Siegmund, D. 1985. Sequential Analysis - Tests and Confidence Intervals. Springer-Verlag, New York.Google ScholarGoogle Scholar
  50. Sinclair, A. 1992. Improved bounds for mixing rates of Markov chains and multicommodity flow. Combin. Probab. Comput. 1, 351--370.Google ScholarGoogle ScholarCross RefCross Ref
  51. Sondow, J. and Weisstein, E. W. Harmonic number. From MathWorld--A Wolfram Web resource. http://mathworld.wolfram.com/HarmonicNumber.html.Google ScholarGoogle Scholar
  52. Voulgaris, S., Gavidia, D., and van Steen, M. 2005. CYCLON: Inexpensive membership management for unstructured P2P overlays. J. Netw. Syst. Manage. 13, 2 (July), 197--217.Google ScholarGoogle ScholarCross RefCross Ref
  53. Watts, D. J. and Strogatz, S. H. 1998. Collective dynamics of small-world networks. Nature 393, 4 (June), 440--442.Google ScholarGoogle ScholarCross RefCross Ref

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  1. RaWMS - Random Walk Based Lightweight Membership Service for Wireless Ad Hoc Networks

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                    John W. Fendrich

                    A random walk is a trajectory made up of a series of random steps. This paper reports on using the results of the topological study of random walks (RWs) on random geometric graphs to model the network connectivity graph of two-dimensional wireless ad hoc networks and sensor networks, to provide network membership services and applications in a novel fashion. It consists of discussions organized into several sections: "Introduction," "System Model," "Random Walk Techniques," "Random Walk Based Membership Services," "Gossip Based Membership Services," "Simulations," "Related Work," and "Discussion and Conclusions." Five appendices discuss "Random Geometric Graphs," "Chernoff Bounds," "Reverse-RW-Based Uniform Sampling with a Proof of an Important Lemma," "Proof of Another Important Lemma," and "Mixing Time Bound for the Maximum Degree Random Walk." The system here is called random walk membership service (RaWMS). It is a novel alternative to other technologies providing membership services. Its uses are asserted to be for data dissemination algorithms, lookup and discovery services, peer sampling services, complete membership construction, and peer-to-peer (P2P) anonymization. The only constraint to the presented strategies and algorithms is the mixing time, the length of the RW in the reverse sampling procedure. There are at least five opportunities for work on open research questions, including analyzing the exact relationship between mobility patterns and the required lengths of random walks (in the paper, this is done only by simulations). A discovery is that shorter RWs obtain better results than longer ones. Another opportunity then would be to develop protocols for measuring changes in node proximity in every node. Online Computing Reviews Service

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                    • Published in

                      cover image ACM Transactions on Computer Systems
                      ACM Transactions on Computer Systems  Volume 26, Issue 2
                      June 2008
                      92 pages
                      ISSN:0734-2071
                      EISSN:1557-7333
                      DOI:10.1145/1365815
                      Issue’s Table of Contents

                      Copyright © 2008 ACM

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                      Publication History

                      • Published: 1 June 2008
                      • Accepted: 1 May 2008
                      • Revised: 1 February 2007
                      • Received: 1 August 2006
                      Published in tocs Volume 26, Issue 2

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