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Wireless Networks
Erschienen in: Wireless Networks 1/2017

16.12.2015

Fault detection and recovery scheme for routing and lifetime enhancement in WSN

verfasst von: M. Yuvaraja, M. Sabrigiriraj

Erschienen in: Wireless Networks | Ausgabe 1/2017

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Abstract

In WSNs, failures are unavoidable due to the inhospitable environment and unattended deployment. The node failure leads to disconnection from the network and causes network partitioning. We propose to develop a fault detection and recovery scheme where the sink generates an agent packet and the Agent forms a query path towards the dead or faulty node. Here, sink periodically broadcasts the Agent packet to all its neighbor nodes. The receiving node randomly makes a decision as whether to forward the packet or not thereby detecting the dead or faulty nodes. After detecting a node failure or dead node, the connectivity is restored using Least-Disruptive Topology Repair (LeDiR) without extending the length of the shortest path among nodes compared to the pre failure topology. LeDiR replaces the faulty node with block movement.
Vorheriger Artikel Energy harvesting and battery power based routing in wireless sensor networks
Nächster Artikel Heterogeneous network bandwidth management scheme based on the principal-agent game model

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Literatur
1.
Wang, C. F., Shih, J. D., Pan, B. H., & Wu, T. Y. (2014). A network lifetime enhancement method for sink relocation and its analysis in wireless sensor networks. IEEE Sensors Journal, 14(6), 1932–1943.CrossRef
2.
Wang, H., Zhang, X., & Khokhar, A. (2007). Efficient “void” handling in contention-based geographic routing for wireless sensor networks. In IEEE global telecommunications conference GLOBECOM.
3.
Han, K., et al. (2013). Algorithm design for data communications in duty-cycled wireless sensor networks: A survey. IEEE Communications Magazine, 51(7), 107–113.CrossRef
4.
Yao, Y., et al. (2013). EDAL: An energy-efficient, delay-aware, and lifetime-balancing data collection protocol for wireless sensor networks. In MASS (pp. 182–190).
5.
Sheng, Z., et al. (2013). A survey on the ietf protocol suite for the internet of things: standards, challenges, and opportunities. Wireless Communications, IEEE., 20(6), 91–98.CrossRef
6.
Zhang, K., Wang, C., & Wang, C. (2008). A secure routing protocol for cluster-based wireless sensor networks using group key management. In 4th International conference on wireless communications, networking and mobile computing, WiCOM.
7.
Kang, K. D., Liu, K., & Abu-Ghazaleh, N. (2006). Securing geographic routing in wireless sensor networks. In 9th Annual cyber security conference on information assurance.
8.
Yu, P., Jia, S., & Xi-yuan, P. (2011). A self detection technique in fault management in WSN. In IEEE instrumentation and measurement technology conference (I2MTC).
9.
Wei, L., et al. (2010). SecCloud: Bridging secure storage and computation in cloud. In ICDCS Workshops (pp. 52–61).
10.
Yan, Z., et al. (2014). A survey on trust management for internet of things. Journal of Network and Computer Applications, 42, 120–134.CrossRef
11.
Jing, Q., et al. (2014). Security of the internet of things: Perspectives and challenges. Wireless Networks, 20(8), 2481–2501.CrossRef
12.
Zhang, Z., et al. (2012). ECG-cryptography and authentication in body area networks. IEEE Transactions on Information Technology in Biomedicine, 16(6), 1070–1078.CrossRef
13.
Zhang, Y., et al. (2013). A real-time dynamic key management for hierarchical wireless multimedia sensor network. Multimedia tools and applications, 67(1), 97–117.CrossRef
14.
Xu, X., et al. (2015). Hierarchical data aggregation using compressive sensing (HDACS) in WSNs. ACM Transactions on Sensor Networks (TOSN)., 11(3), 45.MathSciNetCrossRef
15.
Xiang, L., et al. (2011). Compressed data aggregation for energy efficient wireless sensor networks. In SECON (pp. 46–54).
16.
Campana, T., & O’Hare, G. M. (2013). Intellectus: multi-hop fault detection methodology. In International conference on selected topics in mobile and wireless networking (MoWNeT).
17.
Liu, X.-Y., et al. (2015). CDC: Compressive data collection for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 26(8), 2188–2197.CrossRef
18.
Fadlullah, Z. M., et al. (2010). DTRAB: combating against attacks on encrypted protocols through traffic-feature analysis. IEEE/ACM Transactions on Networking (TON), 18(4), 1234–1247.CrossRef
19.
Abu Alsheikh, M., Lin, S., Niyato, D., & Tan, H. P. (2014). Machine learning in wireless sensor networks: Algorithms, strategies, and applications. Communications Surveys and Tutorials, IEEE, 16(4), 1996–2018.CrossRef
20.
He, D., et al. (2012). ReTrust: Attack-resistant and lightweight trust management for medical sensor networks. IEEE Transactions on Information Technology in Biomedicine, 16(4), 623–632.CrossRef
21.
Xiao, Y., et al. (2012). Tight performance bounds of multihop fair access for MAC protocols in wireless sensor networks and underwater sensor networks. IEEE Transactions on Mobile Computing, 11(10), 1538–1554.CrossRef
22.
Wei, G., et al. (2011). Prediction-based data aggregation in wireless sensor networks: Combining grey model and Kalman filter. Computer Communications, 34(6), 793–802.CrossRef
23.
Wei, L., et al. (2014). Security and privacy for storage and computation in cloud computing. Information Sciences, 258, 371–386.CrossRef
24.
Rehena, Z., Mukherjee, R., Roy, S., & Mukherjee, N. (2014). Detection of node failure in wireless sensor networks. Applications and innovations in mobile computing (AIMoC).
25.
He, Daojing, et al. (2012). A distributed trust evaluation model and its application scenarios for medical sensor networks. IEEE Transactions on Information Technology in Biomedicine, 16(6), 1164–1175.CrossRef
26.
Yang, Haomin, et al. (2014). Provably secure three-party authenticated key agreement protocol using smart cards. Computer Networks, 58, 29–38.CrossRef
27.
Yan, Z., et al. (XXXX). A security and trust framework for virtualized networks and software‐defined networking. In Security and communication networks.
28.
Yin, X., et al. (XXXX). Keep all mobile users′ whereabouts secure: A radio frequency identification protocol anti‐tracking. In 5G international journal of communication systems.
29.
Abbasi, A. A., Younis, M. F., & Baroudi, U. A. (2013). Recovering from a node failure in wireless sensor-actor networks with minimal topology changes. IEEE Transactions on Vehicular Technology, 62(1), 256–271.CrossRef
30.
31.
Afsar, M. M. (2014). Maximizing the reliability of clustered sensor networks by a fault-tolerant service. In IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE).
32.
Szczytowski, P., Khelil, A., & Suri, N. (2012). DKM: Distributed k-connectivity maintenance in wireless sensor networks. In 9th Annual conference on wireless on-demand network systems and services (WONS).
33.
Da Silva, R. I., Macedo, D. F., & Nogueira, J. M. S. (2012). Fault tolerance in spatial query processing for wireless sensor networks. In IEEE Network Operations and Management Symposium (NOMS).
34.
Lee, S., & Younis, M. (2010). Recovery from multiple simultaneous failures in wireless sensor networks using minimum Steiner tree. Journal of Parallel and Distributed Computing, 70(5), 525–536.CrossRefMATH
35.
Guan, Z., Gao, Z., Yang, Y., Li, Y., & Qiu, X. (2010). A distributed fault recovery method in clustering-based wireless sensor networks. In Proceedings of AIAI2010 (pp. 269–273).
36.
Senel, F., Younis, M. F., & Akkaya, K. (2011). Bio-inspired relay node placement heuristics for repairing damaged wireless sensor networks. IEEE Transactions on Vehicular Technology, 60(4), 1835–1848.CrossRef
37.
Akkaya, K., Senel, F., Thimmapuram, A., & Uludag, S. (2010). Distributed recovery from network partitioning in movable sensor/actor networks via controlled mobility. IEEE Transactions on Computers, 59(2), 258–271.MathSciNetCrossRef
38.
Han, X., Cao, X., Lloyd, E. L., & Shen, C. C. (2010). Fault-tolerant relay node placement in heterogeneous wireless sensor networks. IEEE Transactions on Mobile Computing, 9(5), 643–656.CrossRef
Metadaten
Titel
Fault detection and recovery scheme for routing and lifetime enhancement in WSN
verfasst von
M. Yuvaraja
M. Sabrigiriraj
Publikationsdatum
16.12.2015
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 1/2017
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-015-1141-7

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