A Survey of Energy Conservation, Routing and Coverage in Wireless Sensor Networks

  • Wang Bin
  • Li Wenxin
  • Li Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6890)


The emergence of multimedia wireless sensor networks and its characteristics bring in new problems of wireless sensor networks compared with the traditional networks and wireless networks. We mainly consider three issues in this paper, energy conservation, coverage and efficient routing, all of which are fundamental in designing and implementation of wireless sensor networks. Energy conservation is the most significant problem in wireless sensor networks due to its limited energy source intuitively. The other two issues are usually combined with the energy conservation problem. The goal of coverage requirement is to have each location in the targeted physical space within sensing range of at least one sensor node. Besides, efficient routing aims to solve the problem that the collected data are efficiently reported to end-users. We introduce several state-of-the-art works and conclude these researches concerning their various metrics. Finally, we propose some rules while designing the wireless sensor networks according to the previous works, concerning these metrics.


Sensor Network Sensor Node Wireless Sensor Network Energy Conservation Network Lifetime 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Adlakha, S., Srivastava, M.: Critical density thresholds for coverage in wireless sensor networks. In: Tachikawa, K. (ed.) Proc. of the IEEE Wireless Communications and Networking (WCNC), pp. 1615–1620. IEEE Press, New Orleans (2003)Google Scholar
  2. 2.
    Al-Karaki, J., Kamal, A.: On the optimal data aggregation and in-network processing based routing in wireless sensor networks, technical report, Iowa State University (2003)Google Scholar
  3. 3.
    Cardei, M., Du, D.-Z.: Improving wireless sensor network lifetime through power aware organization. Wireless Networks 11(3), 333–340 (2005)CrossRefGoogle Scholar
  4. 4.
    Cardei, M., MacCallum, D., Cheng, X., Min, M., Jia, X., Li, D., Du, D.-Z.: Wireless sensor networks with energy efficient organization. J. Interconnection Networks 3(3-4), 213–229 (2002)CrossRefGoogle Scholar
  5. 5.
    Chakrabarty, K., Lyengar, S.S., Qi, H., Cho, E.: Grid coverage for surveillance and target location in distributed sensor networks. IEEE Trans. on Computers 51(12), 1448–1453 (2002)CrossRefMathSciNetGoogle Scholar
  6. 6.
    Chang, J.-H., Tassiulas, L.: Maximum lifetime routing in wireless sensor networks. In: Proc. Adv. Telecommun. Inf. Distribution Res. Program (ATIRP 2000), College Park, MD (March 2000)Google Scholar
  7. 7.
    Culler, D., Estrin, D., Srivastava, M.: Guest Editorsapos; Introduction: Overview of Sensor Networks. Computer 37(8), 41–49 (2004)CrossRefGoogle Scholar
  8. 8.
    Gupta, H., Das, S.R., Gu, Q.: Connected sensor cover: Self-Organization of sensor networks for efficient query execution. In: Gerla, M. (ed.) Proc. of the ACM Int’l Symp. on Mobile Ad Hoc Networking and Computing (MobiHOC), pp. 189–200. ACM Press, New York (2003)Google Scholar
  9. 9.
    He, T., Stankovic, J.A., Lu, C., Abdelzaher, T.: SPEED: a stateless protocol for real-time communication in sensor networks. In: Proceedings of International Conference on Distributed Computing Systems, Providence, RI (May 2003)Google Scholar
  10. 10.
    Heinzelman, W., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensor networks. In: Proc. 33rd Hawaii Int. Conf. Syst. Sci, HICSS 2000 (January 2000)Google Scholar
  11. 11.
    Heinzelman, W., Kulik, J., Balakrishnan, H.: Adaptive protocols for information dissemination in wireless sensor networks. In: Proc. 5th ACM/IEEE Mobicom. Conf. (MobiCom 1999), Seattle, WA, pp. 174–185 (August 1999)Google Scholar
  12. 12.
    Intanagonwiwat, C., Govindan, R., Estrin, D.: Directed diffusion for wireless sensor networks. IEEE/ACM Trans. Networking 11(1), 2–16 (2003)CrossRefGoogle Scholar
  13. 13.
    Lindsey, S., Raghavendra, C.: PEGASIS: power-efficient gathering in sensor information systems. In: Int. Conf. Communication Protocols, pp. 149–155 (2001)Google Scholar
  14. 14.
    Liu, L., Hu, B., Li, L.: Algorithms for energy efficient mobile object tracking in wireless sensor networks. Cluster Computing 13, 181–197 (2010)CrossRefGoogle Scholar
  15. 15.
    Liu, L., Hu, B., Li, L.: Energy conservation algorithms for maintaining coverage and connectivity in wireless sensor networks. IET Communications 4, 786–800 (2010)CrossRefMathSciNetGoogle Scholar
  16. 16.
    Liu, L., Li, L., Hu, B.: Algorithms for k-fault Tolerant Power Assignments in Wireless Sensor Networks. Science China-Information Sciences 53(12) (2010)Google Scholar
  17. 17.
    Kalpakis, K., Dasgupta, K., Namjoshi, P.: Maximum lifetime data gathering and aggregation in wireless sensor networks. In: Proceedings of IEEE International Conference on Networking (NETWORKS 2002), Atlanta, GA (August 2002)Google Scholar
  18. 18.
    Kar, K., Banerjee, S.: Node placement for connected coverage in sensor networks. In: Proc. WiOpt 2003: Modeling Optimization Mobile, Ad Hoc Wireless Networks (March 2003)Google Scholar
  19. 19.
    Kulik, J., Heinzelman, W.R., Balakrishnan, H.: Negotiation-based protocols for disseminating information in wireless sensor networks. Wireless Networks 8, 169–185 (2002)CrossRefzbMATHGoogle Scholar
  20. 20.
    Li, L., Halpern, J.Y.: Minimum-energy mobile wireless networks revisited. In: ICC 2001, Helsinki, Finland, pp. 67–78 (June 2001)Google Scholar
  21. 21.
    Li, Q., Aslam, J., Rus, D.: Hierarchical power-aware routing in sensor networks. In: Proc. DIMACS Workshop Pervasive Networking (May 2001)Google Scholar
  22. 22.
    Lin, F., Chiu, P.L.: A near-optimal sensor placement algorithm to achieve complete coverage/discrimination in sensor networks. IEEE Communications Letters 9(1), 43–45 (2005)Google Scholar
  23. 23.
    Lindsey, S., Raghavendra, C.S., Sivalingam, K.: Data gathering in sensor networks using the energy*delay metric. In: Proceedings of the IPDPS Workshop on Issues in Wireless Networks and Mobile Computing, San Francisco, CA (April 2001)Google Scholar
  24. 24.
    Manjeshwar, A., Agarwal, D.P.: APTEEN: a hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks. In: Proc. Int. Parallel Distributed Process. Symp., IPDPS, pp. 195–202 (2002)Google Scholar
  25. 25.
    Manjeshwar, A., Agarwal, D.P.: TEEN: a routing protocol for enhanced efficiency in wireless sensor networks. In: 1st Int. Workshop Parallel Distributed Computing Issues Wireless Networks Mobile Computing (April 2001)Google Scholar
  26. 26.
    Rodoplu, V., Meng, T.H.: Minimum energy mobile wireless networks. IEEE JSAC 17(8), 1333–1344 (1999)Google Scholar
  27. 27.
    Slijepcevic, S., Potkonjak, M.: Power efficient organization of wireless sensor networks. In: Proc IEEE Int. Conf. Commun., Helsinki, Finland, pp. 472–476 (June 2001)Google Scholar
  28. 28.
    Sohrabi, K., Pottie, J.: Protocols for self-organization of a wireless sensor network. IEEE Personal Commun. 7(5), 16–27 (2000)CrossRefGoogle Scholar
  29. 29.
    Tian, D., Georganas, N.D.: A node scheduling scheme for energy conservation in large wireless sensor networks. Wireless Communications and Mobile Computing 3(2), 271–290 (2003)CrossRefGoogle Scholar
  30. 30.
    Xu, Y., Heidemann, J., Estrin, D.: Geography-informed energy conservation for ad-hoc routing. In: IEEE/ACM MobiCom, Rome, July 16-21, pp. 70–84 (2001)Google Scholar
  31. 31.
    Ye, F., Zhong, G., Lu, S., Zhang, L.: Energy efficient robust sensing coverage in large sensor networks. technical report, UCLA (2002)Google Scholar
  32. 32.
    Yu, Y., Estrin, D., Govindan, R.: Geographical and energyaware routing: a recursive data dissemination protocol for wireless sensor networks. UCLA Computer Science Department Technical Report, UCLA-CSD TR-01-0023 (May 2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Wang Bin
    • 1
  • Li Wenxin
    • 1
  • Li Liu
    • 2
  1. 1.Lanzhou Physical InstituteLanzhouP.R. China
  2. 2.School of Information Science and EngineeringLanzhou UniversityLanzhouP.R. China

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