Skip to main content
Log in

Recover Fault Services via Complex Service-to-Node Mappings in Wireless Sensor Networks

  • Published:
Journal of Network and Systems Management Aims and scope Submit manuscript

Abstract

With the motivation of seamlessly extending wireless sensor networks to the external environment, service-oriented architecture comes up as a promising solution. However, as sensor nodes are failure prone, this consequently renders the whole wireless sensor network to seriously faulty. When a particular node is faulty, the service on it should be migrated into those substitute sensor nodes that are in a normal status. Currently, two kinds of approaches exist to identify the substitute sensor nodes: the most common approach is to prepare redundancy nodes, though the involved tasks such as maintaining redundancy nodes, i.e., relocating the new node, lead to an extra burden on the wireless sensor networks. More recently, other approaches without using redundancy nodes are emerging, and they merely select the substitute nodes in a sensor node’s perspective i.e., migrating the service of faulty node to it’s nearest sensor node, though usually neglecting the requirements of the application level. Even a few work consider the need of the application level, they perform at packets granularity and don’t fit well at service granularity. In this paper, we aim to remove these limitations in the wireless sensor network with the service-oriented architecture. Instead of deploying redundancy nodes, the proposed mechanism replaces the faulty sensor node with consideration of the similarity on the application level, as well as on the sensor level. On the application level, we apply the Bloom Filter for its high efficiency and low space costs. While on the sensor level, we design an objective solution via the coefficient of a variation as an evaluation for choosing the substitute on the sensor level.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Iyengar, S.S., Brooks, R.R.: Distributed Sensor Networks: Sensor Networking and Applications, vol. 26. CRC Press, Boca Raton (2012)

    Book  Google Scholar 

  2. Li, S., Xu, L., Wang, X., Wang, J.: Integration of hybrid wireless networks in cloud services oriented enterprise information systems. Enterp. Inf. Syst. 6(2), 165–187 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  3. Li, G., Law, R., Rong, J., Vu, H.Q.: Incorporating both positive and negative association rules into the analysis of outbound tourism in Hong Kong. J. Travel Tour. Mark. 27(8), 812–828 (2010)

    Article  Google Scholar 

  4. Niu, W., Li, G., Zhao, Z., Tang, H., Shi, Z.: Multi-granularity context model for dynamic web service composition. J. Netw. Comput. Appl. 34(1), 312–326 (2011)

    Article  Google Scholar 

  5. Niu, W., Li, G., Tang, H., Zhou, X., Shi, Z.: CARSA: A context-aware reasoning-based service agent model for ai planning of web service composition. J. Netw. Comput. Appl. 34(5), 1757–1770 (2011)

    Article  Google Scholar 

  6. Su, Z., Timmermans, W.J., Tol, C., Dost, R., Bianchi, R., Gómez, J.A., House, A., Hajnsek, I., Menenti, M., Magliulo, V., Esposito, M., Haarbrink, R., Bosveld, F., Rothe, R., Baltink, H.K., Vekerdy, Z., Sobrino, J.A., Timmermans, J., Laake, P., Salama, S., Kwast, H., Claassen, E., Stolk, A., Jia, L., Moors, E., Hartogensis, O., Gillespie, A.: Eagle 2006—multi-purpose, multi-angle and multi-sensor in-situ and airborne campaigns over grassland and forest. Hydrol. Earth Syst. Sci. 13, 833–845 (2009)

    Google Scholar 

  7. Folea, S., Neagu, M., Mois, G., Miclea, L.: Multi-purpose sensor platform development. In: 2012 IEEE International Conference on Automation Quality and Testing Robotics (AQTR), pp. 341–346. IEEE (2012)

  8. Song, G., Gu, H., Mo, Y.L.: Smart aggregates: multi-functional sensors for concrete structuresa tutorial and a review. Smart Mater. Struct. 17, 033001 (2008)

    Article  Google Scholar 

  9. Qian, Y., Lu, K., Tipper, D.: A design for secure and survivable wireless sensor networks. Wirel. Commun. IEEE 14(5), 30–37 (2007)

    Article  Google Scholar 

  10. Xu, K., Howitt, I.: Realistic energy model based energy balanced optimization for low rate WPAN network. In: Southeastcon, 2009, SOUTHEASTCON’09, IEEE, pp. 261–266. IEEE (2009)

  11. Xu, K., Tipmongkonsilp, S., Tipper, D., Qian, Y., Krishnamurthy, P.: A time dependent performance model for multi-hop wireless networks with CBR traffic. In: 29th IEEE International Performance Computing and Communications Conference (IPCCC’10), pp. 271–280. IEEE (2010)

  12. Samina, E., Bechir, H.: A survey on energy-efficient routing techniques with QOS assurances for wireless multimedia sensor networks. IEEE Commun. Surv. Tutor. 14(2), 265–278 (2012)

    Article  Google Scholar 

  13. Xu, K., Zhou, M.: Energy balanced chain in IEEE 802.15. 4 low rate WPAN. In: 2013 International Conference on Computing, Networking and Communications (ICNC), pp. 1010–1015. IEEE (2013)

  14. Van Steen, M.: Distributed systems principles and paradigms. Network 3, 26 (2003)

    Google Scholar 

  15. Anastasi, G., Conti, M., Di Francesco, M., Passarella, A.: Energy conservation in wireless sensor networks: a survey. Ad Hoc Netw. 7(3), 537–568 (2009)

    Article  Google Scholar 

  16. Xu, K., Tipper, D., Krishnamurthy, P., Qian, Y.: An efficient hybrid model and dynamic performance analysis for multihop wireless networks. In: 2013 International Conference on Computing, Networking and Communications (ICNC), pp. 1090–1096. IEEE (2013)

  17. Kim, S., Rodrigo, F., David, C.: Reliable transfer on wireless sensor networks. In: The First IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON 2004), pp. 449–459. IEEE (2004)

  18. Wang, Y., Wu, H.: Delay/fault-tolerant mobile sensor network (DFT-MSN): a new paradigm for pervasive information gathering. IEEE Trans. Mobile Comput. 6(9), 1021–1034 (2007)

    Article  Google Scholar 

  19. Janidarmian, M., Zilic, Z., Radecka, K.: Issues in multi-valued multi-modal sensor fusion. In: 2012 42nd IEEE International Symposium on Multiple-Valued Logic (ISMVL), pp. 238–243. IEEE (2012)

  20. Araújo, F., Rodrigues, L.: On the monitoring period for fault-tolerant sensor networks. In: Dependable Computing, pp. 174–190 (2005)

  21. Cerpa, A., Estrin, D.: ASCENT: Adaptive self-configuring sensor networks topologies. IEEE Trans. Mobile Comput. 3(3), 272–285 (2004)

    Article  Google Scholar 

  22. Sharma, A., Wadhwa, Y., Aggarwal, A.: Routing and computing in wireless sensor networks. Int. J. 3(1), 336–339 (2013)

    Google Scholar 

  23. Oyman, E., Ersoy, C.: Multiple sink network design problem in large scale wireless sensor networks. In: 2004 IEEE International Conference on Communications, vol. 6, pp. 3663–3667. IEEE, (2004)

  24. Broder, A., Mitzenmacher, M.: Network applications of bloom filters: a survey. Internet Math. 1(4), 485–509 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  25. Lovie P. (2005) Coefficient of variation. Encyclopedia of Statistics in Behavioral Science

  26. Ell, K.: Coefficient of variation. Environ. Asp. Trace Elem. Coal 2, 112 (1995)

    Google Scholar 

  27. Paradis, L., Han, Q.: A survey of fault management in wireless sensor networks. Netw. Syst. Manag. 15(2), 171–190 (2007)

    Article  Google Scholar 

  28. Huangshui, H., Guihe, Q.: Fault management frameworks in wireless sensor networks. In: 2011 International Conference on Intelligent Computation Technology and Automation (ICICTA), vol. 2, pp. 1093–1096. IEEE (2011)

  29. Asim, M., Mokhtar, H., Merabti, M.: A self-managing fault management mechanism for wireless sensor networks. ArXiv preprint arXiv:1011.5072 (2010)

    Google Scholar 

  30. Wan, C.-Y., Eisenman, S.B., Campbell, A.T.: CODA: Congestion detection and avoidance in sensor networks. In: Proceedings of the 1st International Conference on Embedded Networked Sensor Systems, pp. 266–279. ACM (2003)

  31. Rajendran, V., Obraczka, K., Yi, Y., Lee, S.-J., Tang, K., Gerla, M.: Combining source-and localized recovery to achieve reliable multicast in multi-hop ad hoc networks. In: NETWORKING 2004. Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communications, pp. 112–124. Springer (2004)

  32. Han, Q., Lazaridis, I., Mehrotra, S., Venkatasubramanian, N.: Sensor data collection with expected reliability guarantees. In: Third IEEE International Conference on Pervasive Computing and Communications Workshops, 2005. PerCom 2005 Workshops, pp. 374–378. IEEE (2005)

  33. Chessa, S., Maestrini, P.: Fault recovery mechanism in single-hop sensor networks. Comput. Commun. 28(17), 1877–1886 (2005)

    Article  Google Scholar 

  34. Koushanfar, F., Potkonjak, M., Sangiovanni-Vincentell, A.: Fault tolerance techniques for wireless ad hoc sensor networks. In: Proceedings of the First IEEE International Conference on Sensors, vol. 2, pp. 1491–1496. IEEE (2002)

  35. Parikh, S., Vokkarane, V.M., Xing, L., Kasilingam, D.: Node-replacement policies to maintain threshold-coverage in wireless sensor networks. In: Proceedings of 16th International Conference on Computer Communications and Networks (ICCCN 2007), pp. 760–765. IEEE (2007)

  36. Dibley, M., Li, H., Yacine, R., Miles, J.: Cost effective and scalable sensor network for intelligent building monitoring. Int. J. Innov. Comput. Inf. Control 8, 12 (2012)

    Google Scholar 

  37. Younis, O., Fahmy, S.: HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans. Mobile Comput. 3(4), 366–379 (2004)

    Article  Google Scholar 

  38. Ye, F., Luo, H., Lu, S., Zhang, L.: Statistical en-route filtering of injected false data in sensor networks. In: Twenty-Third Annual Joint Conference of the IEEE Computer and Communications Societies, vol. 4, pp. 2446–2457. IEEE (2004)

  39. Kirsch, A., Mitzenmacher, M.: Less hashing, same performance: building a better bloom filter. Algorithms–ESA 2006, pp. 456–467 (2006)

  40. Han, J., Kamber, M.: Data Mining: Concepts and Techniques. Morgan Kaufmann, Los Altos (2006)

    Google Scholar 

  41. Yick, J., Mukherjee, B., Ghosal, D.: Wireless sensor network survey. Comput. Netw. 52(12), 2292–2330 (2008)

    Article  Google Scholar 

  42. Murillo, A.F., Pena, M., Martínez, D.: Applications of WSN in health and agriculture. In: 2012 IEEE Colombian Communications Conference (COLCOM), pp. 1–6. IEEE (2012)

  43. Bhavsar, A.R., Shah, D.J., Arolkar, H.A.: Distributed data storage model for cattle health monitoring using WSN. Adv. Comput. Sci. Int. J. 2(2), 19–24 (2013)

    Google Scholar 

  44. Potyrailo, R.A., Nagraj, N., Surman, C., Boudries, H., Lai, H., Slocik, J.M., Kelley-Loughnane, N. Naik, R.R.: Wireless sensors and sensor networks for homeland security applications. TrAC Trends Anal. Chem. 40, 133–145 (2012)

  45. Viani, F., Rocca, P., Oliveri, G., Massa, A.: Pervasive remote sensing through WSNs. In: 2012 6th European Conference on Antennas and Propagation (EUCAP), pp. 49–50. IEEE (2012)

  46. Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, 2000, pp. 10–pp. IEEE (2000)

Download references

Acknowledgments

This work was partially supported by the National Natural Science Foundation of China (No. 61103158), the Strategic Priority Research Program of the Chinese Academy of Sciences Grant (XDA06030200), the National High-Tech Research and Development Plan 863 of China (Grant No. 2011AA010703), the Securing CyberSpaces Research Cluster of Deakin University, Guangxi Key Laboratory of Trusted Software.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Qian Li.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Li, Q., Niu, W., Li, G. et al. Recover Fault Services via Complex Service-to-Node Mappings in Wireless Sensor Networks. J Netw Syst Manage 23, 474–501 (2015). https://doi.org/10.1007/s10922-014-9302-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10922-014-9302-z

Keywords

Navigation