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Growing Fully Distributed Robust Topologies in a Sensor Network

  • Andrea Gasparri
  • Sandro Meloni
  • Stefano Panzieri
Part of the Understanding Complex Systems book series (UCS)

Abstract

Wireless Sensor Networks (WSN) are at the forefront of emerging technologies due to the recent advances in Micro-Electro-Mechanical Systems (MEMS) technology. WSN are considered to be unattended systems with applications ranging from environmental sensing, structural monitoring, and industrial process control to emergency response and mobile target tracking.The distributed nature and the limited hardware capabilities of WSN challenge the development of effective applications. The strength of a sensor network, which turns out to be also its weakness, is the capability to perform inter-node processing while sharing data across the network. However, the limited reliability of a node, due to the low-cost nature of the hardware components, drastically constrains this aspect. For this reason, the availability of a mechanism to build distributed robust connectivity topologies, where robustness is meant against random failures of nodes and intentional attacks of nodes, is crucial. The complex network theory along with the percolation theory provides a suitable framework to achieve that. Indeed, topologies such as multi-modal and scale free ones, show interesting properties which might be embedded into a sensor network to significantly increase its robustness. In this work, a mechanisms to build robust topologies in a distributed fashion is proposed, its effectiveness is analytically investigated and results are validated through simulations.

Keywords

Sensor Network Wireless Sensor Network Degree Distribution Percolation Theory Topology Control 
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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References

  1. 1.
    Bettstetter, C.: On the minimum node degree and connectivity of a wireless multihop network. In: MobiHoc 2002: Proceedings of the 3rd ACM international symposium on Mobile ad hoc networking & computing, pp. 80–91. ACM Press, New York (2002)CrossRefGoogle Scholar
  2. 2.
    Blough, D.M., Leoncini, M., Resta, G., Santi, P.: The k-neighbors approach to interference bounded and symmetric topology control in ad hoc networks. IEEE Trans. Mob. Comput. 5(9), 1267–1282 (2006)CrossRefGoogle Scholar
  3. 3.
    Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., Hwang, D.-U.: Complex networks: Structure and dynamics. Physics Reports 424(4-5), 175–308 (2006)CrossRefMathSciNetGoogle Scholar
  4. 4.
    Borbash, S.A., Jennings, E.H.: Distributed topology control algorithm for multihop wireless networks. In: Proc. 2002 World Congress on Computational Intelligence (WCCI 2002), pp. 355–360 (2002)Google Scholar
  5. 5.
    Cerpa, A., Elson, J., Hamilton, M., Zhao, J., Estrin, D., Girod, L.: Habitat monitoring: application driver for wireless communications technology. In: SIGCOMM LA 2001: Workshop on Data communication in Latin America and the Caribbean, pp. 20–41. ACM Press, New York (2001)CrossRefGoogle Scholar
  6. 6.
    Cohen, R., ben Avraham, D., Havlin, S.: Percolation critical exponents in scale-free networks. Phys. Rev. E 66(3), 036113 (2002)CrossRefGoogle Scholar
  7. 7.
    Cohen, R., Erez, K., ben Avraham, D., Havlin, S.: Resilience of the internet to random breakdowns. Phys. Rev. Lett. 85(21), 4626–4628 (2000)CrossRefGoogle Scholar
  8. 8.
    Datta, M.-A.: A fault-tolerant protocol for energy-efficient permutation routing in wireless networks. IEEE Trans. Comput. 54(11), 1409–1421 (2005)CrossRefGoogle Scholar
  9. 9.
    Deb, B., Nath, B.: On the node-scheduling approach to topology control in ad hoc networks. In: MobiHoc 2005: Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing, pp. 14–26. ACM Press, New York (2005)CrossRefGoogle Scholar
  10. 10.
    Dousse, O., Thiran, P., Hasler, M.: Connectivity in ad-hoc and hybrid networks. In: Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies. IEEE INFOCOM 2002, pp. 1079–1088 (2002)Google Scholar
  11. 11.
    Gupta, P., Kumar, P.R.: Critical power for asymptotic connectivity. In: Proceedings of the 37th IEEE Conference on Decision & Control, pp. 1106–1110 (1998)Google Scholar
  12. 12.
    Hajiaghayi, M.T., Immorlica, N., Mirrokni, V.S.: Power optimization in fault-tolerant topology control algorithms for wireless multi-hop networks. IEEE/ACM Trans. Netw. 15(6), 1345–1358 (2007)CrossRefGoogle Scholar
  13. 13.
    Kim, S., Pakzad, S., Culler, D., Demmel, J., Fenves, G., Glaser, S., Turon, M.: Health monitoring of civil infrastructures using wireless sensor networks. In: IPSN 2007: Proceedings of the 6th international conference on Information processing in sensor networks, pp. 254–263. ACM Press, New York (2007)CrossRefGoogle Scholar
  14. 14.
    Leoncini, M., Resta, G., Santi, P.: The k-neighbors approach to interference bounded and symmetric topology control in ad hoc networks. IEEE Transactions on Mobile Computing 5(9), 1267–1282 (2006); Senior Member-Douglas M. BloughCrossRefGoogle Scholar
  15. 15.
    Lesser, V., Atighetchi, M., Benyo, B., Horling, B., Raja, A., Vincent, R., Wagner, T., Ping, X., Zhang, S.X.Q.: The intelligent home testbed. In: Proceedings of the Autonomy Control Software Workshop (Autonomous Agent Workshop) (January 1999)Google Scholar
  16. 16.
    Li, L., Halpern, J.Y., Bahl, P., Wang, Y.-M., Wattenhofer, R.: A cone-based distributed topology-control algorithm for wireless multi-hop networks. IEEE/ACM Trans. Netw. 13(1), 147–159 (2005)CrossRefGoogle Scholar
  17. 17.
    Li, N., Hou, J.C., Sha, L.: Design and analysis of an mst-based topology control algorithm. In: Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies. IEEE INFOCOM 2003, vol. 3, pp. 1702–1712 (2003)Google Scholar
  18. 18.
    Li, N., Hou, J.C.: Flss: a fault-tolerant topology control algorithm for wireless networks. In: MobiCom 2004: Proceedings of the 10th annual international conference on Mobile computing and networking, pp. 275–286. ACM Press, New York (2004)CrossRefGoogle Scholar
  19. 19.
    Li, N., Hou, J.C.: Localized topology control algorithms for heterogeneous wireless networks. IEEE/ACM Trans. Netw. 13(6), 1313–1324 (2005)CrossRefGoogle Scholar
  20. 20.
    Li, X.-Y., Song, W.-Z., Wang, Y.: Localized topology control for heterogeneous wireless sensor networks. ACM Trans. Sen. Netw. 2(1), 129–153 (2006)CrossRefMathSciNetGoogle Scholar
  21. 21.
    Li, X.-Y., Wan, P.-J., Wang, Y., Yi, C.-W.: Fault tolerant deployment and topology control in wireless networks. In: MobiHoc 2003: Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing, pp. 117–128. ACM Press, New York (2003)CrossRefGoogle Scholar
  22. 22.
    Liang, C., Huang, X., Deng, J.: A fault tolerant and energy efficient routing protocol for urban sensor networks. In: InfoScale 2007: Proceedings of the 2nd international conference on Scalable information systems, ICST, Brussels, Belgium, Belgium, pp. 1–8. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering) (2007)Google Scholar
  23. 23.
    Liang, Q., Wang, L., Ren, Q.: Fault and tolerant and energy efficient cross-layer design for wireless sensor networks. Int. J. Sen. Netw. 2(3/4), 248–257 (2007)CrossRefGoogle Scholar
  24. 24.
    Liu, J., Li, B.: Distributed topology control in wireless sensor networks with asymmetric links. In: Global Telecommunications Conference, 2003. GLOBECOM 2003, vol. 3, pp. 1257–1262 (2003)Google Scholar
  25. 25.
    Mehta, V., El Zarki, M.: A bluetooth based sensor network for civil infrastructure health monitoring. Wirel. Netw. 10(4), 401–412 (2004)CrossRefGoogle Scholar
  26. 26.
    Molloy, M., Reed, B.: The size of the giant component of a random graph with a given degree sequence. Combin. Probab. Comput. 7, 295–305 (1998)zbMATHCrossRefMathSciNetGoogle Scholar
  27. 27.
    Nayebi, A., Sarbazi-Azad, H.: Lifetime analysis of the logical topology constructed by homogeneous topology control in wireless mobile networks. In: International Conference on Parallel and Distributed Systems, vol. 2(5), pp. 1–8 (2007)Google Scholar
  28. 28.
    Patel, S., Lorincz, K., Hughes, R., Huggins, N., Growdon, J.H., Welsh, M., Bonato, P.: Analysis of feature space for monitoring persons with parkinson’s disease with application to a wireless wearable sensor system. In: Proceedings of the 29th IEEE EMBS Annual International Conference, Lyon, France (August 2007)Google Scholar
  29. 29.
    Raghavan, U.N., Kumara, S.R.T.: Decentralised topology control algorithms for connectivity of distributed wireless sensor networks. Int. J. Sen. Netw. 2(3/4), 201–210 (2007)CrossRefGoogle Scholar
  30. 30.
    Santi, P.: Topology control in wireless ad hoc and sensor networks. ACM Comput. Surv. 37(2), 164–194 (2005)CrossRefGoogle Scholar
  31. 31.
    Shnayder, V., Chen, B.r., Lorincz, K., Thaddeus, R.F., Jones, F., Welsh, M.: Sensor networks for medical care. In: SenSys 2005: Proceedings of the 3rd international conference on Embedded networked sensor systems, p. 314. ACM Press, New York (2005)CrossRefGoogle Scholar
  32. 32.
    Srivastava, M.B., Muntz, R.R., Potkonjak, M.: Smart kindergarten: sensor-based wireless networks for smart developmental problem-solving enviroments. In: Mobile Computing and Networking, pp. 132–138 (2001)Google Scholar
  33. 33.
    Stauffer, D., Aharony, A.: Introduction to percolation theory. CRC Press, Boca Raton (1998)Google Scholar
  34. 34.
    Tanizawa, T., Paul, G., Havlin, S., Stanley, H.E.: Optimization of the robustness of multimodal networks. Phys. Rev. E 74(1), 016125 (2006)CrossRefGoogle Scholar
  35. 35.
    Thallner, B., Moser, H., Schmid, U.: Topology control for fault-tolerant communication in wireless ad hoc networks. In: Wireless Networks (2008)Google Scholar
  36. 36.
    Wang, X.F., Chen, G.: Complex networks: small-world, scale-free and beyond. Circuits and Systems Magazine, IEEE 3(1), 6–20 (2003)CrossRefGoogle Scholar
  37. 37.
    Watts, D.J., Strogatz, S.H.: Collective dynamics of ’small-world’ networks. Nature 393(6684), 440–442 (1998)CrossRefGoogle Scholar
  38. 38.
    Werner-Allen, G., Lorincz, K., Welsh, M., Marcillo, O., Johnson, J., Ruiz, M., Lees, J.: Deploying a wireless sensor network on an active volcano. IEEE Internet Computing 10(2), 18–25 (2006)CrossRefGoogle Scholar
  39. 39.
    Xue, F., Kumar, P.R.: The number of neighbors needed for connectivity of wireless networks. Wirel. Netw. 10(2), 169–181 (2004)CrossRefGoogle Scholar
  40. 40.
    Yuanyuan, Z., Medidi, M.: Sleep-based topology control for wakeup scheduling in wireless sensor networks. In: 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, 2007. SECON 2007, June 2007, pp. 304–313 (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Andrea Gasparri
    • 1
  • Sandro Meloni
    • 1
  • Stefano Panzieri
    • 1
  1. 1.University of “Roma Tre”

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