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Cooperative data collection in ad hoc networks

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Abstract

This paper studies the problem of data gathering in multi-hop wireless ad hoc networks. In this scenario, a set of wireless devices constantly sample their surroundings and initiate report messages addressed to the base station. The messages are forwarded in a multi-hop fashion, where the wireless devices act both as senders and relays. We consider data gathering without aggregation, i.e. the nodes are required to forward all the messages initiated by other nodes (in addition to their own) to the base station. This is in contrast to the well studied problem of data gathering with aggregation, which is significantly simpler. As some nodes experience a larger load of forward requests, these nodes will have their battery charges depleted much faster than the other nodes—which can rapidly break the connectivity of the network. We focus on maximizing the network lifetime through efficient balancing of the consumed transmission energy. We show that the problem is NP-hard for two network types and develop various approximation schemes. Our results are validated through extensive simulations.

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Notes

  1. The homogeneous model is better known as the UDG model [2].

References

  1. Bermond, J. C., Nisse, N., Reyes, P., & Rivano, H. (2009). Fast data gathering in radio grid networks. In AlgoTel’09, pp. 53–56.

  2. Buragohain, C., Agrawal, D., & Suri, S. (2005). Power aware routing for sensor databases. In INFOCOM 2005, pp. 1747–1757.

  3. Chehri, A., Fortier, P., & Tardif, P.-M. (2007). Security monitoring using wireless sensor networks. Communication Networks and Services Research, Annual Conference on, 0, 13–17.

    Google Scholar 

  4. Chen, J., Kleinberg, R. D., Lovász, L., Rajaraman, R., Sundaram, R., & Vetta, A. (2007). (almost) tight bounds and existence theorems for single-commodity confluent flows. J ACM, 54, July 2007.

  5. Chen, T.-S., Tsai, H.-W., & Chu, C.-P. (2006). Gathering-load-balanced tree protocol for wireless sensor networks. pp. 8–13.

  6. Chintalapudi, K., Fu, T., Paek, J., Kothari, N., Rangwala, S., Caffrey, J. et al. (2006). Monitoring civil structures with a wireless sensor network. IEEE Internet Computing, 10(2), 26–34.

    Article  Google Scholar 

  7. Ciullo, D., Celik, G. D., & Modiano, E. (2010). Minimizing transmission energy in sensor networks via trajectory control. In WiOpt’10: Modeling and optimization in mobile, ad hoc, and wireless networks, pp. 259–268.

  8. Ford, L. R., & Fulkerson, D. R. (1956). Maximal flow through a network. Canadian Journal of Mathematics, 8, 399–404.

    Article  MathSciNet  MATH  Google Scholar 

  9. Fortune, S. Hopcroft, J. E., & Wyllie, J. C. (1980). The directed subgraph homeomorphism problem. Theoretical Computer Science, 10, 111–121.

    Article  MathSciNet  MATH  Google Scholar 

  10. Gallager, R. G., Humblet, P. A., & Spira, P. M. (1983). A distributed algorithm for minimum-weight spanning trees. ACM Transactions on Programming Languages and Systems, 5, 66–77.

    Article  MATH  Google Scholar 

  11. Garey, M. R., & Johnson, D. S. (1990). Computers and intractability; A guide to the theory of NP-completeness. New York, NY: W. H. Freeman & Co.

    Google Scholar 

  12. Gehrke, J., & Madden, S. (2004). Query processing in sensor networks. IEEE Pervasive Computing, 3(1), 46–55.

    Google Scholar 

  13. Guruswami, V., Khanna, S., Rajaraman, R., Shepherd, B., & Yannakakis, M. (2003). Near-optimal hardness results and approximation algorithms for edge-disjoint paths and related problems. Journal of Computer and System Sciences, 67(3), 473–496.

    Article  MathSciNet  MATH  Google Scholar 

  14. Hekmat, R., & Van Mieghem, P. (2006). Connectivity in wireless ad-hoc networks with a log-normal radio model. Mobile Network Applications, 11, 351–360.

    Article  Google Scholar 

  15. Hoebeke, J., Moerman, I., Dhoedt, B., & Demeester, P. (2004). An overview of mobile ad hoc networks: Applications and challenges. Journal of the Communications Network, 3, 60–66.

    Google Scholar 

  16. Wei, H.-y., & Gitlin, R. D. (2004). Two-hop-relay architecture for next generation wwan/wlan integration. IEEE Wireless Communications (Special Issue on 4G Mobile Communications-Towards Open Wireless Architecture), 11, 24–30.

    Google Scholar 

  17. Kalpakis, K., Dasgupta, K., & Namjoshi, P. (2003). Efficient algorithms for maximum lifetime data gathering and aggregation in wireless sensor networks. Computer Networks, 42, 697–716.

    Article  MATH  Google Scholar 

  18. King, V., Rao, S., & Tarjan, R. (1992). A faster deterministic maximum flow algorithm, pp. 157–164.

  19. Kolchin, V. F., Sevastianov, B. A., & Chistiakov, V. P. (1978). Random allocations. Washington, New York: V. H. Winston; (distributed solely by Halsted Press).

  20. Kulik, J., Heinzelman, W., & Balakrishnan, H. (2002). Negotiation-based protocols for disseminating information in wireless sensor networks. Wireless Networks, 8, 169–185.

    Article  MATH  Google Scholar 

  21. Lenstra, J. K., Shmoys, D. B., & Tardos, É. (1990). Approximation algorithms for scheduling unrelated parallel machines. Math. Program., 46(3), 259–271.

    Article  MathSciNet  MATH  Google Scholar 

  22. Lessmann, J., & Krishnamurthy, A. (2007). Parameterized hierarchical layer topology construction for wireless networks. In ICSNC ’07: Proceedings of the second international conference on systems and networks communications, p. 15. IEEE Computer Society.

  23. Levin, L., Segal, M., & Shpungin, H. (2010). Optimizing performance of ad-hoc networks under energy and scheduling constraints. In WiOpt’10: Modeling and optimization in mobile, ad hoc, and wireless networks, pp. 110–119.

  24. Liang, J., Wang, J., Cao, J., Chen, J., & Lu, M. (2010) An efficient algorithm for constructing maximum lifetime tree for data gathering without aggregation in wireless sensor networks. In Proceedings of the 29th conference on Information communications, INFOCOM’10 (pp. 506–510). New York: IEEE Press.

  25. Lin, C.-S., Huang, C.-N., & Fang, R.-J. (2008) A power-efficient data gathering scheme on grid sensor networks. In Proceedings of the 8th WSEAS international conference on multimedia systems and signal processing, pp. 142–147. World Scientific and Engineering Academy and Society (WSEAS).

  26. Liu, A.-F., Wu, X.-Y., Chen, Z.-G., & Gui, W.-H. (2010). An energy-balanced data gathering algorithm for linear wireless sensor networks. International Journal of Wireless Information Networks, 17, 42–53.

    Article  Google Scholar 

  27. Liu, Y. (2007). Online data gathering for maximizing network lifetime in sensor networks. IEEE Transactions on Mobile Computing, 6(1), 2–11.

    Article  Google Scholar 

  28. Mainwaring, A., Culler, D., Polastre, J., Szewczyk, R., & Anderson, J. (2002). Wireless sensor networks for habitat monitoring. In WSNA ’02: Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications, pp. 88–97.

  29. Mhatre, V., & Rosenberg, C. (2004). Homogeneous vs. heterogeneous clustered sensor networks: A comparative study. In In Proceedings of 2004 IEEE international conference on communications (ICC 2004, pp. 3646–3651.

  30. Pahlavan, K., & Levesque, A. H. (1995). Wireless Information Networks.

  31. Segal, M. (2008). Fast algorithm for multicast and data gathering in wireless networks. Information Processing Letters, 107(1), 29–33.

    Article  MathSciNet  MATH  Google Scholar 

  32. Segal, M., & Shpungin, H. (2009). On construction of minimum energy k-fault resistant topologies. Ad Hoc Networks, 7(2), 363–373.

    Article  Google Scholar 

  33. Shpungin, H., & Segal, M. (2009). Near optimal multicriteria spanner constructions in wireless ad-hoc networks. IEEE/ACM Transaction on Networking.

  34. Stanford, J., & Tongngam, S. (1998). Approximation algorithm for maximum lifetime in wireless sensor networks with data aggregation. In FOCS 1998, pp. 300–309.

  35. Stoumpos, V., Deligiannakis, A., Kotidis, Y., & Delis, A. (2008). Processing event-monitoring queries in sensor networks. In Proceedings of the 2008 IEEE 24th international conference on data engineering, pp. 1436–1438. IEEE Computer Society.

  36. Sundaresan, K., & Rangarajan, S. (2008). On exploiting diversity and spatial reuse in relay-enabled wireless networks. pp. 13–22.

  37. Woo, A., Tong, T., & Culler, D. (2003). Taming the underlying challenges of reliable multihop routing in sensor networks. In SenSys ’03: Proceedings of the 1st international conference on Embedded networked sensor systems (pp. 14–27). New York, NY: ACM.

  38. Wu, Y., Fahmy, S., & Shroff, N. B. (2008). On the construction of a maximum-lifetime data gathering tree in sensor networks: Np-completeness and approximation algorithm. In INFOCOM (pp. 356–360).

  39. Zhang, H., Shen, H., & Tian, H. (2006). Reliable and real-time data gathering in multi-hop linear wireless sensor networks. In Cheng, X., Li, W., Znati, T. (Eds.), Wireless algorithms, systems, and applications, volume 4138 of lecture notes in computer science (pp. 151–162). Berlin: Springer.

  40. Zhang, L., & Soong, B.-H. (2005). Interference distribution in the Nakagami fading wireless CDMA ad hoc networks with multi-code multi-packet transmission (MCMPT). In 30th annual IEEE conference on local computer networks (LCN 2005), 15–17 November 2005, Sydney, Australia, Proceedings. IEEE Computer Society.

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Acknowledgments

The authors would like to thank Refael Hassin and the anonymous reviewers for their valuable suggestions and helpful comments.

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Authors and Affiliations

  1. Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Liron Levin, Michael Segal & Hanan Shpungin

Authors
  1. Liron Levin
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  2. Michael Segal
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  3. Hanan Shpungin
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Corresponding author

Correspondence to Michael Segal.

Additional information

A preliminary version of this paper has appeared in WiOPT’10 [23]. The work on this paper has been partially supported by US Air Force European Office of Aerospace Research and Development, grant #FA8655-09-1-3016, Deutsche Telecom, European project FLAVIA and Israeli Ministry of Industry, Trade and Labor (consortium CORNET). Liron Levin and Michael Segal are with the Dept. of Communication Systems Engineering, Ben-Gurion University of the Negev, Israel. Hanan Shpungin is with the Dept. of Electrical and Computer Engineering, University of Waterloo, Canada.

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Levin, L., Segal, M. & Shpungin, H. Cooperative data collection in ad hoc networks. Wireless Netw 19, 145–159 (2013). https://doi.org/10.1007/s11276-012-0456-x

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