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A trajectory-based selective broadcast query protocol for large-scale, high-density wireless sensor networks

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Abstract

We present a small-footprint search protocol designed to facilitate any-type queries for data content and services in large population, high-density wireless sensor networks. Our protocol, termed Trajectory-based Selective Broadcast Query (TSBQ), works in conjunction with time division multiple access- or schedule-based medium access control protocols to reduce per-query energy expenditure. We compare the performance of TSBQ to unicast- and local broadcast-based search algorithms and also determine a critical node density based on the energy expended by nodes to transmit and receive. Minimal energy expenditure is achieved by determining the optimal number of data/service replicates and the number of nodes designated to receive each query transmission. Numerical results indicate that TSBQ significantly reduces the total energy expenditure of a network as compared to unicast and local broadcast-based search protocols.

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References

  1. Banka, T., Tandon, G., & Jayasumana, A. (2005). Zonal rumor routing for wireless sensor networks. In Proceedings of the international conference on information technology: coding and computing (Vol. 2, pp. 562–567).

  2. Bellavista, P., Corradi, A., & Magistretti, E. (2005). Comparing and evaluating lightweight solutions for replica dissemination and retrieval in dense MANETs. In Proceedings of the 10th IEEE symposium on computers and communications (pp. 43–50).

  3. Bisnik, N., & Abouzeid, A. (2005). Modeling and analysis of random walk search algorithms in P2P networks. In Proceedings of the second international workshop on hot topics in peer-to-peer systems (pp. 95–103).

  4. Braginsky, D., & Estrin, D. (2002). Rumor routing algorithm for sensor networks. In Proceedings of the 1st ACM international workshop on wireless sensor networks and applications (pp. 22–31).

  5. Chen, B., Jamieson, K., Balakrishnan, H., & Morris, R. (2002). Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks. Wireless Networks, 8(5), 481–494.

    Article  Google Scholar 

  6. Chou, C. F., Su, J. J., & Chen, C. Y. (2005). Straight line routing for wireless sensor networks. In Proceedings of the 10th IEEE symposium on computers and communications (pp. 110–115).

  7. Cohen, E., & Shenker, S. (2002). Replication strategies in unstructured peer-to-peer networks. In Proceedings of the 2002 conference on applications, technologies, architectures, and protocols for computer communications (pp. 177–190).

  8. Gaeta, R., Balbo, G., Bruell, S., Gribaudo, M., & Sereno, M. (2005). A simple analytical framework to analyze search strategies in large-scale peer-to-peer networks. Performance Evaluation, 62(1–4), 1–16.

    Google Scholar 

  9. Gkantsidis, C., Mihail, M., & Saberi, A. (2005). Hybrid search schemes for unstructured peer-to-peer networks. In Proceedings of the 24th annual joint conference of the IEEE computer and communications societies (Vol. 3, pp. 1526–1537).

  10. Heidemann, J., Bulusu, N., Elson, J., Intanagonwiwat, C., Lan, K., & Xu, Y. et al. (2001). Effects of detail in wireless network simulation. In Proceedings of the SCS multiconference on distributed simulation (pp. 3–11).

  11. Karp, B., & Kung, H. T. (2000). GPSR: Greedy perimeter stateless routing for wireless networks. In Proceedings of the 6th annual international conference on mobile computing and networking (pp. 243–254).

  12. Liu, D., Hu, X., & Jia, X. (2006). Energy efficient protocols for information dissemination in wireless sensor networks. In Lecture notes in computer science (Vol. 3842, pp. 176–185).

  13. Lu, G., Krishnamachari, B., & Raghavendra, C. (2004). An adaptive energy-efficient and low-latency MAC for data gathering in sensor networks. In Proceedings of the 18th international parallel and distributed processing symposium (p. 224).

  14. Malkhi, D., Naor, M., & Ratajczak, D. (2002). Viceroy: A scalable and dynamic emulation of the butterfly. In Proceedings of the 21st annual symposium on principles of distributed computing (pp. 183–192).

  15. Manku, G. S., Naor, M., & Wieder, U. (2004). Know thy neighbor’s neighbor: The power of lookahead in randomized P2P networks. In Proceedings of the 36th annual ACM symposium on theory of computing (pp. 54–63).

  16. Melamed, R., Keidar, I., & Barel, Y. (2005). Octopus: A fault-tolerant and efficient ad-hoc routing protocol. In Proceedings of the 24th IEEE symposium on reliable distributed systems (pp. 39–49).

  17. Nath, B., & Niculescu, D. (2003). Routing on a curve. ACM SIGCOMM Computer Communication Review, 33(1), 155–160.

    Article  Google Scholar 

  18. Rajendran, V., Obraczka, K., & Garcia-Luna-Aceves, J. J. (2006). Energy-efficient, collision-free medium access control for wireless sensor networks. Wireless Networks, 12(1), 63–78.

    Article  Google Scholar 

  19. Ratnasamy, S., Francis, P., Handley, M., Karp, R., & Schenker, S. (2001). A scalable content-addressable network. New York: ACM Press.

    Google Scholar 

  20. Ratnasamy, S., Karp, B., Yin, L., Yu, F., Estrin, D., & Govindan, R. et al. (2002). GHT: A geographic hash table for data-centric storage. In Proceedings of the 1st ACM international workshop on wireless sensor networks and applications (pp. 78–87).

  21. Ratnasamy, S., Karp, B., Shenker, S., Estrin, D., Govindan, R., & Yin, L. et al. (2003). Data-centric storage in sensornets with GHT, A geographic hash table. Mobile Networks and Applications, 8(4), 427–442.

    Article  Google Scholar 

  22. Rowstron, A., & Druschel, P. (2001). Pastry: Scalable, distributed object location and routing for large-scale peer-to-peer systems. In IFIP/ACM international conference on distributed systems platforms (middleware) (pp. 329–350).

  23. Shenker, S., Ratnasamy, S., Karp, B., Govindan, R., & Estrin, D. (2003). Data-centric storage in sensornets. Computer Communication Review, 33(1), 137–142.

    Article  Google Scholar 

  24. Stoica, I., Morris, R., Karger, D., Kaashoek, M. F., & Balakrishnan, H. (2001). Chord: A scalable peer-to-peer lookup service for internet applications. Proceedings of the 2001 SIGCOMM conference, 31(4), 149–160.

    Google Scholar 

  25. Stojmenovic, I. (1999). A scalable quorum based location update scheme for routing in ad hoc wireless networks (TR 99-09). SITE, University of Ottawa.

  26. Stojmenovic, I., & Lin, X. (2001). Loop-free hybrid single-path/flooding routing algorithms with guaranteed delivery for wireless networks. IEEE Transactions on Parallel and Distributed Systems, 12(10), 1023–1032.

    Article  Google Scholar 

  27. Tchakarov, J. B., & Vaidya, N. H. (2004). Efficient content location in wireless ad hoc networks. In Proceedings of the 2004 IEEE international conference on mobile data management (pp. 74–85).

  28. van Dam, T., & Langendoen, K. (2003). An adaptive energy-efficient MAC protocol for wireless sensor networks. In Proceedings of the 1st international conference on embedded networked sensor systems (pp. 171–180).

  29. Xu, Y., Heidemann, J., & Estrin, D. (2001). Geography-informed energy conservation for ad hoc routing. In Proceedings of the 7th annual international conference on mobile computing and networking (pp. 70–84).

  30. Xue, F., & Kumar, P. R. (2006). On the θ-coverage and connectivity of large random networks. In IEEE/ACM Transactions on Networking (TON), (Vol. 14, pp. 2289–2299).

  31. Ye, W., Heidemann, J., & Estrin, D. (2002). An energy-efficient MAC protocol for wireless sensor networks. In Proceedings of the 21st annual joint conference of the ieee computer and communications societies (Vol. 3, pp. 1567–1576).

  32. Zhang, H., & Hou, J. (2004). On deriving the upper bound of α-lifetime for large sensor networks. In Proceedings of the 5th ACM international symposium on mobile ad hoc networking and computing (pp. 121–132).

  33. Zhao, B. Y., Kubiatowicz, J., & Joseph, A. D. (2001). Tapestry: An infrastructure for fault-tolerant wide-area location and routing (Tech. Rep. UCB/CSD-01-1141). Computer Science Division, University of California, Berkley.

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Correspondence to Christopher R. Mann.

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The views expressed in this paper are those of the authors and do not reflect the official policy or position of the United States Air Force, Department of Defense, or the U.S. government.

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Mann, C.R., Baldwin, R.O., Kharoufeh, J.P. et al. A trajectory-based selective broadcast query protocol for large-scale, high-density wireless sensor networks. Telecommun Syst 35, 67–86 (2007). https://doi.org/10.1007/s11235-007-9041-5

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