Abstract
In Wireless Sensor Networks (WSN), cluster formation and cluster head selection are critical issues. They can drastically affect the network’s performance in different environments with different characteristics. In order to deal with this problem, we have proposed a fuzzy-based system for cluster-head selection and controlling sensor speed in Wireless Sensor Networks (WSNs). The proposed system is constructed by two Fuzzy Logic Controllers (FLC). We use four input linguistic parameters for evaluating lifetime of a sensor in FLC1. Then, we use the output of FLC1 and two other linguistic parameters as input parameters of FLC2 to control the probability of headcluster selection. By considering the moving speed of the sensor we are able to predict whether the node will leave or stay in the cluster. In this paper, we evaluate FLC1 and FLC2 by simulations and show that they have a good behavior.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: a survey. Comput Netw 38(4):393–442
Akyildiz IF, Kasimoglu IH (2004) Wireless sensor and actor networks: research challenges. Ad Hoc Netw 2(4):351–367
Giordano S, Rosenberg C (2006) Topics in ad hoc and sensor networks. IEEE Commun Mag 44(4):97
Al-Karaki JN, Kamal AE (2004) Routing techniques in wireless sensor networks: a survey. IEEE Wirel Commun 11(6):6–28
Chatterjee M, Das SK, Turgut D (2002) Wca: a weighted clustering algorithm for mobile ad hoc networks. J Cluster Comput 5(2):193–204
Banerjee S, Khuller S (2001) A clustering scheme for hierarchical control in multi-hop wireless networks. In: Proceedings of IEEE INFOCOM-2001, pp 1028–1037
Chen WP, How JC, Sha L (2004) Dynamic clustering for acoustic target tracking in wireless sensor networks. IEEE Trans Mob Comput 3(3):258–271
Basagni S (1999) Distributed clustering for ad hoc networks. In: International symposium of parallel architectures, algorithms and networks (I-SPAN’99), pp 310–315
Amis AD, Prakash R, Vuong THP, Huynh DT (2000) Max–min d-cluster formation in wireless ad hoc networks. In: Proceedings of IEEE INFOCOM-2000, pp 32–41
Chan H, Perrig A (2004) Ace: an emergent algorithm for highly uniform cluster formation. In: Proceedings of European workshop on wireless sensor networks (EWSN-2004) pp 154–171
Heinzelman WB, Chandrakasan AP, Balakrishnan H (2004) An application-specific protocol architecture for wireless microsensor networks. IEEE Trans Wireless Commun 1(4):660–670
Heinzelman WR, Chandrakasan A, Balakrishnan H (2000) Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd annual Hawaii international conference on system sciences (HICSS) pp 3005–3014
Lindsey S, Raghavendra C, Sivalingam KM (2002) Data gathering algorithms in sensor networks using energy metrics. IEEE Trans Parallel Distrib Syst 13(9):924–935
Chan PML, Sheriff RE, Hu Y, Conforto P, Tocci C (2001) Mobility management incorporating fuzzy logic for a heterogeneous ip environment. IEEE Commun Mag 39(12):42–51
Barolli L, Koyama A, Suganuma T, Shiratori N (2003) Gaman: a ga based qos routing method for mobile adhocnetworks. J Interconnect Netw (JOIN) 4(3):251–270
Wang Q, Ando H, Kulla E, Barolli L, Durresi A (2012) A fuzzy-based cluster-head selection system for WSNs considering different parameters. In: Proceedings of the 26th international conference on advanced information networking and applications workshops (WAINA’12), pp 962–967
Wang Q, Barolli L, Kulla E, Durresi A, Biberaj A, Takizawa M (2012) A fuzzy-based simulation system for controlling sensor speed in wireless sensor networks. In: Proceedings of 15th international conference on network-based information systems (NBiS’12), pp 208–213
Liang Q (2003) A design methodology for wireless personal area networks with power efficiency. In: Proceedings of the wireless communications and networking (WCNC), vol 3, pp 1475–1480
Anno J, Barolli L, Xhafa F, Durresi A (2007) A cluster head selection method for wireless sensor networks based on fuzzy logic. In: Proceedings of IEEE TENCON-2007, CD–ROM, 4 p
Anno J, Barolli L, Durresi A, Xhafa F, Koyama A (2008) A cluster head decision system for sensor networks using fuzzy logic and number of neighbor nodes. In: Proceedings of IEEE Ubi-media 2008, pp 50–56
Anno J, Barolli L, Xhafa F, Durresi A, Koyama A (2008) Performance evaluation of two-fuzzy based cluster head selection systems for wireless sensor networks. J Mobile Inf Syst (MIS) 4(4):297–312
Mendel JM (1995) Fuzzy logic systems for engineering: a tutorial. Proc IEEE 83(3):345–377
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media Dordrecht
About this paper
Cite this paper
Wang, Q., Barolli, L., Kulla, E., Mino, G., Ikeda, M., Iwashige, J. (2013). Considering Lifetime of Sensors for Clusterhead Selection in WSN Using Fuzzy Logic. In: Park, J., Barolli, L., Xhafa, F., Jeong, HY. (eds) Information Technology Convergence. Lecture Notes in Electrical Engineering, vol 253. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6996-0_30
Download citation
DOI: https://doi.org/10.1007/978-94-007-6996-0_30
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-6995-3
Online ISBN: 978-94-007-6996-0
eBook Packages: EngineeringEngineering (R0)