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Erschienen in: Wireless Personal Communications 1/2014

01.09.2014

Choice of Detection Parameters on Fault Detection in Wireless Sensor Networks: A Multiobjective Optimization Approach

verfasst von: Arunanshu Mahapatro, Ajit Kumar Panda

Erschienen in: Wireless Personal Communications | Ausgabe 1/2014

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Abstract

In this paper, the intermittent fault detection in wireless sensor networks is formulated as an optimization problem and a recently introduced multiobjective swarm optimization (2LB-MOPSO) algorithm is used to find an optimum trade-off between detection accuracy and detection latency. Faulty sensor nodes are identified based on comparisons of sensed data between one-hop neighboring nodes. Time redundancy is used to detect intermittent faults since an intermittent fault does not occur consistently. Simulation and analytical results show that sensor nodes with permanent faults are identified with high accuracy and by properly choosing the inter-test interval most of the intermittent faults are isolated with negligible performance degradation.

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Fußnoten
1
Faults are classified as: crash, omission, timing, and Byzantine. Crash faults are hard faults, and all others can be treated as soft faults.
 
2
Perfect test: a fault is always detected by the test when it occurs, and is isolated.
 
Literatur
1.
Zurück zum Zitat Gao, J.-L., Xu, Y.-J., & Li, X. W. (May 2007). Weighted-median based distributed fault detection for wireless sensor networks. Journal of Software, 18(5), 1208–1217. Gao, J.-L., Xu, Y.-J., & Li, X. W. (May 2007). Weighted-median based distributed fault detection for wireless sensor networks. Journal of Software, 18(5), 1208–1217.
2.
Zurück zum Zitat Mahapatro, A., & Khilar, P. (2013). Fault diagnosis in wireless sensor networks: A survey. Communications Surveys Tutorials, IEEE, 15(4), 2000–2026.CrossRef Mahapatro, A., & Khilar, P. (2013). Fault diagnosis in wireless sensor networks: A survey. Communications Surveys Tutorials, IEEE, 15(4), 2000–2026.CrossRef
3.
Zurück zum Zitat Serafini, M., Bondavalli, A., & Suri, N. (2007). On-line diagnosis and recovery: On the choice and impact of tuning parameters. IEEE Transactions on Dependable and Secure Computing, 4(4), 295–312.CrossRef Serafini, M., Bondavalli, A., & Suri, N. (2007). On-line diagnosis and recovery: On the choice and impact of tuning parameters. IEEE Transactions on Dependable and Secure Computing, 4(4), 295–312.CrossRef
4.
Zurück zum Zitat Sedighi, T., Phillips, P., & Foote, P. D. (2013). Model-based intermittent fault detection. Procedia CIRP 11, 68–73. Sedighi, T., Phillips, P., & Foote, P. D. (2013). Model-based intermittent fault detection. Procedia CIRP 11, 68–73.
5.
Zurück zum Zitat Zhao, S. Z., & Suganthan, P. N. (2011). Two-lbests based multi-objective particle swarm optimizer. Engineering Optimization, 43(1), 1–17.MathSciNetCrossRef Zhao, S. Z., & Suganthan, P. N. (2011). Two-lbests based multi-objective particle swarm optimizer. Engineering Optimization, 43(1), 1–17.MathSciNetCrossRef
6.
Zurück zum Zitat Dhillon, J. S., Parti, S. C., & Kothari, D. P. (1993). Stochastic economic emission load dispatch. Electric Power Systems Research, 26(3), 179–186.CrossRef Dhillon, J. S., Parti, S. C., & Kothari, D. P. (1993). Stochastic economic emission load dispatch. Electric Power Systems Research, 26(3), 179–186.CrossRef
7.
Zurück zum Zitat Chessa, S., & Santi, P. (2002). Crash faults identification in wireless sensor networks. Computer Communications, 25(14), 1273–1282.CrossRef Chessa, S., & Santi, P. (2002). Crash faults identification in wireless sensor networks. Computer Communications, 25(14), 1273–1282.CrossRef
8.
Zurück zum Zitat Chen, J., Kher, S., & Somani, A. (2006) Distributed fault detection of wireless sensor networks. In Proceedings of the 2006 workshop on dependability issues in wireless ad hoc networks and sensor networks, New York, NY, USA, ACM, pp. 65–72. Chen, J., Kher, S., & Somani, A. (2006) Distributed fault detection of wireless sensor networks. In Proceedings of the 2006 workshop on dependability issues in wireless ad hoc networks and sensor networks, New York, NY, USA, ACM, pp. 65–72.
9.
Zurück zum Zitat Jiang, P. (2009). A new method for node fault detection in wireless sensor networks. Sensors, 9(2), 1282–1294.CrossRef Jiang, P. (2009). A new method for node fault detection in wireless sensor networks. Sensors, 9(2), 1282–1294.CrossRef
10.
Zurück zum Zitat Elhadef, M., Boukerche, A., & Elkadiki, H. (2008). A distributed fault identification protocol for wireless and mobile ad hoc networks. Journal Parallel Distributed Computing, 68, 321–335.MATHCrossRef Elhadef, M., Boukerche, A., & Elkadiki, H. (2008). A distributed fault identification protocol for wireless and mobile ad hoc networks. Journal Parallel Distributed Computing, 68, 321–335.MATHCrossRef
11.
Zurück zum Zitat Miao, X., Liu, K., He, Y., Liu, Y., & Papadias, D. (2011). Agnostic diagnosis: Discovering silent failures in wireless sensor networks. In INFOCOM, pp. 1548–1556. Miao, X., Liu, K., He, Y., Liu, Y., & Papadias, D. (2011). Agnostic diagnosis: Discovering silent failures in wireless sensor networks. In INFOCOM, pp. 1548–1556.
12.
Zurück zum Zitat Kim, D. J., & Prabhakaran, B. (2011). Motion fault detection and isolation in body sensor networks. Pervasive and Mobile Computing, 7(6), 727–745.CrossRef Kim, D. J., & Prabhakaran, B. (2011). Motion fault detection and isolation in body sensor networks. Pervasive and Mobile Computing, 7(6), 727–745.CrossRef
13.
Zurück zum Zitat Wang, W., Wang, B., Liu, Z., & Guo, L. (2011). A cluster-based real-time fault diagnosis aggregation algorithm for wireless sensor networks. Information Technology Journal, 10(1), 80–88.MathSciNetCrossRef Wang, W., Wang, B., Liu, Z., & Guo, L. (2011). A cluster-based real-time fault diagnosis aggregation algorithm for wireless sensor networks. Information Technology Journal, 10(1), 80–88.MathSciNetCrossRef
14.
Zurück zum Zitat Babaie, S., Khosrohosseini, A., & Khadem-Zadeh, A. (2013). A new self-diagnosing approach based on petri nets and correlation graphs for fault management in wireless sensor networks. Journal of Systems Architecture, 59(8), 582–600.CrossRef Babaie, S., Khosrohosseini, A., & Khadem-Zadeh, A. (2013). A new self-diagnosing approach based on petri nets and correlation graphs for fault management in wireless sensor networks. Journal of Systems Architecture, 59(8), 582–600.CrossRef
15.
Zurück zum Zitat Lee, M. H., & Choi, Y. H. (2008). Fault detection of wireless sensor networks. Computer Communications, 31(14), 3469–3475.CrossRef Lee, M. H., & Choi, Y. H. (2008). Fault detection of wireless sensor networks. Computer Communications, 31(14), 3469–3475.CrossRef
16.
Zurück zum Zitat Khilar, P., & Mahapatra, S. (2007). Intermittent fault diagnosis in wireless sensor networks. In 10th International conference on information, technology, pp. 145–147. Khilar, P., & Mahapatra, S. (2007). Intermittent fault diagnosis in wireless sensor networks. In 10th International conference on information, technology, pp. 145–147.
17.
Zurück zum Zitat Xu, X., Chen, W., Wan, J., & Yu, R. (November 2008). Distributed fault diagnosis of wireless sensor networks. In 11th IEEE International conference on communication, technology, pp. 148–151. Xu, X., Chen, W., Wan, J., & Yu, R. (November 2008). Distributed fault diagnosis of wireless sensor networks. In 11th IEEE International conference on communication, technology, pp. 148–151.
18.
Zurück zum Zitat Yim, S. J., & Choi, Y. H. (2010). An adaptive fault-tolerant event detection scheme for wireless sensor networks. Sensors, 10(3), 2332–2347.CrossRef Yim, S. J., & Choi, Y. H. (2010). An adaptive fault-tolerant event detection scheme for wireless sensor networks. Sensors, 10(3), 2332–2347.CrossRef
19.
Zurück zum Zitat Ji, Z., Bing-shu, W., Yong-guang, M., Rong-hua, Z., & Jian, D. (October 2006). Fault diagnosis of sensor network using information fusion defined on different reference sets. In International conference on Radar, pp. 1–5. Ji, Z., Bing-shu, W., Yong-guang, M., Rong-hua, Z., & Jian, D. (October 2006). Fault diagnosis of sensor network using information fusion defined on different reference sets. In International conference on Radar, pp. 1–5.
20.
Zurück zum Zitat Jabbari, A., Jedermann, R., & Lang, W. (2007). Application of computational intelligence for sensor fault detection and isolation. In World academy of science, engineering and technology, pp. 265–270. Jabbari, A., Jedermann, R., & Lang, W. (2007). Application of computational intelligence for sensor fault detection and isolation. In World academy of science, engineering and technology, pp. 265–270.
21.
Zurück zum Zitat Moustapha, A., & Selmic, R. (2008). Wireless sensor network modeling using modified recurrent neural networks: Application to fault detection. IEEE Transactions on Instrumentation and Measurement, 57(5), 981–988.CrossRef Moustapha, A., & Selmic, R. (2008). Wireless sensor network modeling using modified recurrent neural networks: Application to fault detection. IEEE Transactions on Instrumentation and Measurement, 57(5), 981–988.CrossRef
22.
Zurück zum Zitat Zhang, X. L., Zhang, F., Yuan, J., lan Weng, J., & Hua Zhang, W. (August 2010). Sensor fault diagnosis and location for small and medium-scale wireless sensor networks. In Sixth international conference on natural computation, pp. 3628–3632. Zhang, X. L., Zhang, F., Yuan, J., lan Weng, J., & Hua Zhang, W. (August 2010). Sensor fault diagnosis and location for small and medium-scale wireless sensor networks. In Sixth international conference on natural computation, pp. 3628–3632.
23.
Zurück zum Zitat Chenglin, Z., Xuebin, S., Songlin, S., & Ting, J. (2011). Fault diagnosis of sensor by chaos particle swarm optimization algorithm and support vector machine. Expert Systems with Applications, 38(8), 9908–9912.CrossRef Chenglin, Z., Xuebin, S., Songlin, S., & Ting, J. (2011). Fault diagnosis of sensor by chaos particle swarm optimization algorithm and support vector machine. Expert Systems with Applications, 38(8), 9908–9912.CrossRef
24.
25.
Zurück zum Zitat Chen, Y., & Zhao, Q. (2005). On the lifetime of wireless sensor networks. IEEE Communications Letters, 9(11), 976–978.CrossRef Chen, Y., & Zhao, Q. (2005). On the lifetime of wireless sensor networks. IEEE Communications Letters, 9(11), 976–978.CrossRef
26.
Zurück zum Zitat Awwad, S., Ng, C., Noordin, N., & Rasid, M. (2011). Cluster based routing protocol for mobile nodes in wireless sensor network. Wireless Personal Communications, 61(2), 251–281.CrossRef Awwad, S., Ng, C., Noordin, N., & Rasid, M. (2011). Cluster based routing protocol for mobile nodes in wireless sensor network. Wireless Personal Communications, 61(2), 251–281.CrossRef
27.
Zurück zum Zitat Guo, S., Zhong, Z., & He, T. (2009). Find: Faulty node detection for wireless sensor networks. In Proceedings of the 7th ACM conference on embedded networked sensor systems, ACM, New York, NY, USA, pp. 253–266. Guo, S., Zhong, Z., & He, T. (2009). Find: Faulty node detection for wireless sensor networks. In Proceedings of the 7th ACM conference on embedded networked sensor systems, ACM, New York, NY, USA, pp. 253–266.
28.
Zurück zum Zitat Vuran, M. C., Akan, O. B., & Akyildiz, I. F. (2004). Spatio-temporal correlation: Theory and applications for wireless sensor networks. Computer Networks, 45(3), 245–259.MATHCrossRef Vuran, M. C., Akan, O. B., & Akyildiz, I. F. (2004). Spatio-temporal correlation: Theory and applications for wireless sensor networks. Computer Networks, 45(3), 245–259.MATHCrossRef
29.
Zurück zum Zitat Ji, S., Fang Yuan, S., Huai Ma, T., & Tan, C. (April 2010). Distributed fault detection for wireless sensor based on weighted average. In Second international conference on networks security wireless communications and trusted computing vol. 1, pp. 57–60. Ji, S., Fang Yuan, S., Huai Ma, T., & Tan, C. (April 2010). Distributed fault detection for wireless sensor based on weighted average. In Second international conference on networks security wireless communications and trusted computing vol. 1, pp. 57–60.
30.
Zurück zum Zitat Mahapatro, A., & Khilar, P. M. (2011). Sddp: Scalable distributed diagnosis protocol for wireless sensor networks. In Contemporary computing. Volume 168 of communications in computer and information science (pp. 69–80). Berlin: Springer. Mahapatro, A., & Khilar, P. M. (2011). Sddp: Scalable distributed diagnosis protocol for wireless sensor networks. In Contemporary computing. Volume 168 of communications in computer and information science (pp. 69–80). Berlin: Springer.
31.
Zurück zum Zitat Mahapatro, A., & Khilar, P. (2012). Online distributed fault diagnosis in wireless sensor networks. Wireless Personal Communications, pp. 1–30. Mahapatro, A., & Khilar, P. (2012). Online distributed fault diagnosis in wireless sensor networks. Wireless Personal Communications, pp. 1–30.
32.
Zurück zum Zitat Breuer, M. (1973). Testing for intermittent faults in digital circuits. IEEE Transactions on Computers, C–22(3), 241–246.MathSciNetCrossRef Breuer, M. (1973). Testing for intermittent faults in digital circuits. IEEE Transactions on Computers, C–22(3), 241–246.MathSciNetCrossRef
33.
Zurück zum Zitat Siewiorek, D. P., & Swmlz, R. S. (1992). Reliable computer system design and evaluation. Bedford, MA: Digital Press. Siewiorek, D. P., & Swmlz, R. S. (1992). Reliable computer system design and evaluation. Bedford, MA: Digital Press.
34.
Zurück zum Zitat Su, S. Y. H., Koren, I., & Malaiya, Y. K. (1978). A continuous-parameter markov model and detection procedures for intermittent faults. IEEE Transactions on Computers, C–27(6), 567–570.CrossRef Su, S. Y. H., Koren, I., & Malaiya, Y. K. (1978). A continuous-parameter markov model and detection procedures for intermittent faults. IEEE Transactions on Computers, C–27(6), 567–570.CrossRef
35.
Zurück zum Zitat Barlow, R. E., & Prochan, F. (1965). Mathematical theory of reliability. London: Wiley.MATH Barlow, R. E., & Prochan, F. (1965). Mathematical theory of reliability. London: Wiley.MATH
36.
Zurück zum Zitat Deb, K. (2001). Multi-objective optimization using evolutionary algorithms. London: Wiley.MATH Deb, K. (2001). Multi-objective optimization using evolutionary algorithms. London: Wiley.MATH
37.
Zurück zum Zitat Abido, M.A. (2007). Two-level of nondominated solutions approach to multiobjective particle swarm optimization. In Proceedings of the 9th annual conference on genetic and evolutionary computation, ACM, pp. 726–733. Abido, M.A. (2007). Two-level of nondominated solutions approach to multiobjective particle swarm optimization. In Proceedings of the 9th annual conference on genetic and evolutionary computation, ACM, pp. 726–733.
38.
Zurück zum Zitat Coello, C. A. C., Pulido, G. T., & Lechuga, M. S. (2004). Handling multiple objectives with particle swarm optimization. IEEE Transactions on Evolutionary Computation, 8(3), 256–279.CrossRef Coello, C. A. C., Pulido, G. T., & Lechuga, M. S. (2004). Handling multiple objectives with particle swarm optimization. IEEE Transactions on Evolutionary Computation, 8(3), 256–279.CrossRef
39.
Zurück zum Zitat Zielinski, K., & Laur, R. (September 2007). Differential evolution with adaptive parameter setting for multi-objective optimization. In Evolutionary computation, 2007. CEC 2007. IEEE Congress on, pp. 3585–3592. Zielinski, K., & Laur, R. (September 2007). Differential evolution with adaptive parameter setting for multi-objective optimization. In Evolutionary computation, 2007. CEC 2007. IEEE Congress on, pp. 3585–3592.
40.
Zurück zum Zitat Zhou, A., Qu, B. Y., Li, H., Zhao, S. Z., Suganthan, P. N., & Zhang, Q. (2011). Multiobjective evolutionary algorithms: A survey of the state of the art. Swarm and Evolutionary Computation, 1(1), 32–49.CrossRef Zhou, A., Qu, B. Y., Li, H., Zhao, S. Z., Suganthan, P. N., & Zhang, Q. (2011). Multiobjective evolutionary algorithms: A survey of the state of the art. Swarm and Evolutionary Computation, 1(1), 32–49.CrossRef
Metadaten
Titel
Choice of Detection Parameters on Fault Detection in Wireless Sensor Networks: A Multiobjective Optimization Approach
verfasst von
Arunanshu Mahapatro
Ajit Kumar Panda
Publikationsdatum
01.09.2014
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 1/2014
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-014-1776-1

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