Abstract
Energy conservation is the most significant issue in wireless sensor networks due to limited power sources of sensor nodes that cannot be recharged or replaced. Clustering is considered to be energy-efficient in WSN as it reduces the number of sensor nodes taking part in long range communication. During clustering, each sensor node selects a cluster head (CH) to join a cluster among several candidate CHs. The selection of cluster head uses different parameters such as residual energy of cluster head and distance between node and cluster head. A poor selection of cluster head will lead to increased energy consumption in network that will degrade the network lifetime. Furthermore, sensor nodes are likely to fail due to different factors such as limited energy and environment hazards. So, the fault tolerance is another challenge for long run of the WSNs. In this paper, we propose a distributed fault-tolerant multi-objective clustering algorithm (DFMCA). In this algorithm, each sensor takes its decision using local information only. We also propose a recovery algorithm in case of sudden death of the cluster heads in the network. A simulation result demonstrates that our algorithm outperforms the existing state-of-the-art algorithms, namely FTCA and LBCA, in terms of network lifetime.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Akilidz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: survey. Comput Netw 38:393–422
Smaragdakis G, Matta I, Bestavros A (2004) SEP: a stable election protocol for clustered heterogeneous wireless sensor networks. In: Second international workshop on sensor and actor network protocols and applications SANPA
Duan C, Fan H (2007) A distributed energy balance clustering protocol for heterogeneous wireless sensor networks, wireless communications, networking and mobile computing. In: WiCom international conference, pp 2469–2473
Qing L, Zhu Q, Wang M (2006) Design of a distributed energy efficient clustering algorithm for heterogeneous wireless sensor networks. Comput Commun 29:2230–2237
Pratyay K, Jana PK (2012) Energy efficient load-balanced clustering algorithm for wireless sensor network. In: ICCCS, Procedia Technology (Elsevier), vol 6, pp 771–777
Heinzelman WB, Chandrakasan A, Balakrishnan H (2000) Energy-efficient communication protocols for wireless microsensor networks. In: Proceedings of Hawaii international conference on system sciences
Lindsey S, Raghavenda CS (2002) PEGASIS: power efficient gathering in sensor information systems. In: Proceeding of the IEEE aerospace conference. Big Sky, Montana
Younis O, Fahmy S (2004) HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans Mobile Comput 3:366–379
Manjeshwar A, Grawal DP (2001) TEEN: a protocol for enhanced efficiency in wireless sensor networks. In: Proceedings of the 15th parallel and distributed processing symposium. IEEE Computer Society, 2011, San Francisco, pp 2009–2015
Gupta G, Younis M (2003) Load-balanced clustering of wireless sensor networks. In: IEEE International Conference ICC ’03, vol 3, pp 1848–1852
Gupta G, Younis M (2003) Fault-tolerant clustering of wireless sensor networks. IEEE WCNC 3:1579–1584
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Mazumdar, N., Om, H. (2017). A Distributed Fault-Tolerant Multi-objective Clustering Algorithm for Wireless Sensor Networks. In: Nath, V. (eds) Proceedings of the International Conference on Nano-electronics, Circuits & Communication Systems. Lecture Notes in Electrical Engineering, vol 403. Springer, Singapore. https://doi.org/10.1007/978-981-10-2999-8_10
Download citation
DOI: https://doi.org/10.1007/978-981-10-2999-8_10
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-2998-1
Online ISBN: 978-981-10-2999-8
eBook Packages: EngineeringEngineering (R0)