Abstract
Sensor nodes in wireless sensor network (WSN) have batteries with a short lifespan and so the energy has to be judiciously utilized. Consumption of transmission energy of nodes that are deployed far away from base station (BS) increases with increase in distance. To prolong the network lifetime, the selection of cluster heads (CH) plays a crucial role. This paper proposes an enhanced zone stable election protocol based on fuzzy logic for cluster head election. The studies on ZSEP-E have assumed probabilistic election of cluster heads in the zones taking into consideration the maximum residual energy of the nodes lacking the studies on diverse parameters for cluster head election. In this paper, fuzzy logic is adapted to ZSEP-E to evaluate the cluster head selection probability taking into account the factors such as residual energy of the node, density, and distance to the base station. Simulation results demonstrate that the proposed method has significant effectiveness in terms of energy consumption as well as maximizing network lifetime by comparing the performance with ZSEP-E and other related works.








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Akyildiz, F., Su, W., Sankarasubramaniam, Y., Cayirici, E.: Wireless sensor network: a survey. Comput. Netw. 38(4), 393–422 (2002)
Haenggi, M.: Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems. CRC Press, Boca Raton (2005)
Chong, C.Y., Kumar, S.P.: Sensor networks: evolution, opportunities, and challenges. Proc. IEEE 91(8), 1247–1256 (2003)
Estrin, D., Girod, L., Pottie, G., Srivastava, M.: Instrumenting the world with wireless sensor networks. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP’01), pp. 2033–2036 (2001)
Chang, C.Y., Chang, H.R.: Energy-aware node placement, topology control and MAC scheduling for wireless sensor networks. Comput. Netw. 52(11), 2189–2204 (2008)
Qing, L., Zhu, Q., Wang, M.: Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks. Comput. Commun. 29, 2230–2237 (2006)
Bhattacharyya, D., Kim, T.-H., Pal, S.: A comparative study of wireless sensor networks and their routing protocols. Sensors 10(12), 10506–10523 (2010)
Ren, X., Yu, H.: Multipath disjoint routing algorithm for ad hoc wireless sensor networks. In: Proceedings of the 8th IEEE International Symposium on Object-Oriented Real-Time Distributed Computing (ISORC’05), pp. 253–256, May 2005
Yick, J., Mukherjee, B., Ghosal, D.: Wireless sensor network survey. Comput. Netw. 52(12), 2292–2330 (2008)
Akkaya, K., Younis, M.: A survey on routing protocols for wireless sensor networks. Ad HocNetworks 3(3), 325–349 (2005)
Liu, X.: A survey on clustering routing protocols in wireless sensor networks. Sensors 12(8), 11113–11153 (2012)
Abbasi, A.A., Younis, M.: A survey on clustering algorithms for wireless sensor networks. Comput. Commun. 30(14–15), 2826–2841 (2007)
Liu, T., Li, Q., Liang, P.: An energy-balancing clustering approach for gradient-based routing in wireless sensor networks. Comput. Commun. 35(17), 2150–2161 (2012)
Heinzelman, W., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless micro sensor networks. In: Proceedings of the 33rd Annual Hawaii International Conference on System Sciences (HICSS), Maui, pp. 3005–3014, Jan 2000
Lindsey, S., Raghavendra, C.: PEGASIS: power-efficient gathering in sensor information systems. In: IEEE Aerospace Conference Proceedings, vol 3, pp. 1125–1130 (2002)
Manjeshwar, A., Agrawal, D.: TEEN: a protocol for enhanced efficiency in wireless sensor networks. In: Proceedings of the 1st International Workshop on Parallel and Distributed Computing Issues in Wireless Networks and Mobile Computing, San Francisco, April 2001
Younis, O., Fahmy, S.: Heed: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans. Mob. Comput. 3(4), 366–379 (2004)
Manjeshwar, A., Agrawal, D.P.: APTEEN: a hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks. In: Parallel and Distributed Processing Symposium, pp. 195–201 (2002)
Heinzelman, W., Chandrakasan, A., Balakrishnan, H.: An application-specific protocol architecture for wireless micro sensor networks. IEEE Trans. Wirel. Commun. 1(4), 660–670 (2002)
Soro, S., Heinzelman, W.B.: Prolonging the lifetime of wireless sensor networks via unequal clustering. In: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS’05), pp. 236–243, Washington, D.C., April 2005
Mary, S.A.S.A., Gnanadurai, J.B.: A zone-based clustering protocol for wireless sensor networks. In: 9th International Conference on Computer Engineering and Applications, pp. 151–161, Dubai, Feb 2015
Zanakis, S.H., Solomon, A., Wishart, N., Dublish, S.: Multiattribute decision making: a simulation comparison of select methods”. Eur. J. Oper. Res. 107(3), 507–529 (1998)
Zopounidis, C., Doumpos, M.: Multicriteria classification and sorting methods: a literature review. Eur. J. Oper. Res. 138(2), 229–246 (2002)
Jahan, A., Mustapha, F., Ismail, M.Y., Sapuan, S.M., Bahraminasab, M.: A comprehensive VIKOR method for material selection. Mater. Des. 32(3), 1215–1221 (2011)
Chauhan, A., Vaish, R.: Pareto optimal microwave dielectric materials. Adv. Sci. Eng. Med. 5(2), 149–155 (2013)
Yang, T., Hung, C.C.: Multiple-attribute decision making methods for plant layout design problem. Robot. Comput. Integr. Manuf. 23(1), 126–137 (2007)
Rathod, M.K., Kanzaria, H.V.: A methodological concept for phase change material selection based on multiple criteria decision analysis with and without fuzzy environment. Mater. Des. 32(6), 3578–3585 (2011)
Torfi, F., Farahani, R.Z.: Rezapour S (2010) Fuzzy AHP to determine the relative weights of evaluation criteria and fuzzy TOPSIS to rank the alternatives. Appl. Soft Comput. J. 10(2), 520–528 (2010)
Padmanabhan, K., Kamalakkannan, P.: A study on energy efficient routing protocols in wireless sensor networks. Eur. J. Sci. Res. 60(4), 499–511 (2011)
Yu, Y., Govindan, R., Estrin, D.: Geographical and energy aware routing: a recursive data dissemination protocol for wireless sensor networks. Technical report UCLA/CSD-TR-01-0023, UCLA Computer Science Department (2001)
Rodoplu, V., Meng, T.H.: Minimum energy mobile wireless networks. IEEE J. Sel. Areas Commun. 17(8), 1333–1344 (1999)
Xu, Y., Heidemann, J., Estrin, D.: Geography-informed energy conservation for ad-hoc routing. In: Proceedings of ACM/IEEE MobiCom’01 pp. 70–84, Rome (2001)
Lindsey, S., Raghavendra, C.S., Sivalingam, K.M.: Data gathering algorithms in sensor networks using energy metrics. IEEE Trans. Parallel Distrib. Syst. 13(9), 924–935 (2002)
Sohrabi, K., Gao, J., Ailawadhi, V., Pottie, G.J.: Protocols for self-organization of a wireless sensor network. IEEE J. Pers. Commun. 7(5), 16–27 (2000)
He, T., Stankovic, J.A., Chenyang, L., Abdelzaher, T.: SPEED: a stateless protocol for real-time communication in sensor networks. In: Proceedings of International Conference on Distributed Computing Systems, pp. 46–55, Providence (2003)
Heinzelman, W.R., Kulik, J., Balakrishnan, H.: Adaptive protocols for information dissemination in wireless sensor networks. In: Proceedings of ACM MobiCom’99, pp. 174–185, Seattle (1999)
Kulik, J., Heinzelman, W., Balakrishnan, H.: Negotiation-based protocols for disseminating information in wireless sensor networks. Wirel. Netw. 8(2/3), 169–185 (2002)
Intanagonwiwat, C., Govindan, R., Estrin, D.: Directed diffusion: a scalable and robust communication paradigm for sensor networks. In: Proceedings ACM MobiCom’00, pp. 56–67, Boston, August 2000
Smaragdakis, G., Matta, I., Bestavros, A.: SEP: a stable election protocol for clustered heterogeneous wireless sensor networks. In: Second International Workshop on Sensor and Actor Network Protocols and Applications (2004)
Younis, O., Fahmy, S.: An experimental study of energy-efficient routing and data aggregation in sensor networks. In: Proceedings of International Workshop on Localized Communication and Topology Protocols for Ad hoc Networks (LOCAN) (pp. 50–57), Nov 2005
Huang, H., Wu, J.: A probabilistic clustering algorithm in wireless sensor networks. In: Vehicular Technology Conference IEEE 62nd VTC-Fall, vol. 3, pp. 1796–1798 (2003)
Khedo, K.K., Subramanian, R.K.: MiSensehierarchial cluster based routing algorithm (MiCRA) for wireless sensor networks. World Acad. Sci. Eng. Technol. 52, 190–195 (2009)
Faisal, S., Javaid, N., Javaid, A., Khan, M.A., Bouk, S.H., Khan, Z.A.: Z-SEP: zonal-stable election protocol for wireless sensor networks. J. Basic Appl. Sci. Res. 3(5), 132–139 (2013)
VenkateswarluKumaramangalam, M., Adiyapatham, K., Kandasamy, C.: Zone-based routing protocol for wireless sensor networks. Int. Sch. Res. Not. vol. 2014, Article ID 798934. doi:10.1155/2014/798934 (2014)
Gupta, I., Riordan, D., Sampalli, S.: Cluster-head election using fuzzy logic for wireless sensor networks. In: Communication Networks and Services Research Conference, pp. 255–260, May 2005
Kim, J., Park, S., Han, Y., Chung, T.: CHEF: cluster head election mechanism using fuzzy logic in wireless sensor networks. In: 10th International Conference on Advanced Communication Technology, ICACT 2008, pp. 654–659, Feb 2008
Lee, J.S., Cheng, W.L.: Fuzzy-logic-based clustering approach for wireless sensor networks using energy predication. IEEE Sens. J. 11(9), 2891–2897 (2012)
Mhemed, R., Aslam, N., Phillips, W., Comeau, F.: An energy efficient fuzzy logic cluster formation protocol in wireless sensor networks. Elsevier Proc. Comput. Sci. 10, 255–262 (2012)
Mamdani, E.H.: Application of fuzzy logic to approximate reasoning using linguistic synthesis. IEEE Trans. Comput. C-26, 1182–1191 (1977)
Yadav, R., Saxena, S.: Improved leach routing protocol with soft computing. In: Second International Conference on Advances in Computing and Communication Engineering (ICACCE), pp. 261–266 (2015)
Krishnan, A.M., Kumar, P.G.: An effective clustering approach with data aggregation using multiple mobile sinks for heterogeneous WSNs. Int. J. Wirel. Pers. Commun. pp. 1–12 (2015)
Rana, S., Bahar, A.N., Islam, N., Islam, J.: Fuzzy based energy efficient multiple cluster head selection routing protocol for wireless sensor networks. Int. J. Comput. Netw. Inf. Secur. 4, 54–61 (2015). doi:10.5815/ijcnis.2015.04.07
Nayak, P., Devulapalli, A.: A fuzzy logic-based clustering algorithm for WSN to extend the network lifetime. IEEE Sens. J. 16(1), 137–144 (2016)
Pal, R., Sharma, A.K.: FSEP-E: enhanced stable election protocol based on fuzzy logic for cluster head selection in WSNs. In: Sixth International Conference on Contemporary Computing, pp. 427–432, Aug 2013
Sharma, T., Kumar, B.: F-MCHEL: fuzzy based master cluster head election leach protocol in wireless sensor network. Int. J. Comput. Sci. Telecommun. 3(10), 8–13 (2012)
Dutta, R., Gupta, S., Das, M.K.: Low-energy adaptive unequal clustering protocol using fuzzy c-Means in wireless sensor networks. Int. J. Wirel. Pers. Commun. 77(14), 1187–1209 (2014)
Zhou, G., He, T., Stankovic, J.A., Abdelzaher, T.: RID: radio interference detection in wireless sensor networks. INFOCOM (2005)
Jiang, H., Sun, Y., Sun, R., Xu, H.: Fuzzy-logic-based energy optimized routing for wireless sensor networks. Int. J. Distrib. Sens. Netw. (2013). doi:10.1155/2013/216561
Barua, A., Mudunuri, L.S., Kosheleva, O.: Why trapezoidal and triangular membership functions work so well: towards a theoretical explanation. J. Uncertain Syst. 8(3), 164–168 (2014)
Acknowledgments
This research was conducted while the second author is a Phd Student in Anna University, Chennai, India. The authors would like to thank the editor and anonymous referees for their valuable comments to improve the quality of this paper.
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A preliminary version of this paper appeared in CEA ’15, Feb 22-24, 2015, WSEAS Press. This extended version is a Fuzzy-based approach to select the CHs in the zones and communication of the aggregated data to the BS.
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Sahaaya Arul Mary, S.A., Gnanadurai, J.B. Enhanced Zone Stable Election Protocol based on Fuzzy Logic for Cluster Head Election in Wireless Sensor Networks. Int. J. Fuzzy Syst. 19, 799–812 (2017). https://doi.org/10.1007/s40815-016-0181-1
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DOI: https://doi.org/10.1007/s40815-016-0181-1