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Wireless Personal Communications
Published in: Wireless Personal Communications 2/2020

15-05-2020

Cross-Layer Energy Based Clustering Technique for Heterogeneous Wireless Sensor Networks

Authors: Sukhchandan Randhawa, Sushma Jain

Published in: Wireless Personal Communications | Issue 2/2020

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Abstract

Increasing the lifetime of the network is one of the key research issues in Wireless Sensor Networks. Sensor nodes residing in hot spot locations get drained out of energy very quickly, which leads to disruption in operations of the network. Thus, a cluster-based algorithm for increasing energy efficiency is required to extend the lifetime of the network. In this research work, Cross-layer Energy based Clustering (CEC) technique is proposed to form clusters of sensor nodes in hexagonal shape. The cluster head has opted from the members of cluster itself on the basis of the ideal cluster head distance and the remaining energy of sensor nodes. In order to make a balance between the consumption of energy and the network traffic, the rotation of cluster heads is performed dynamically. The energy level of a node also gets affected due to collisions happening during the transmissions. These collisions can be prevented by applying protocols which are free of contention. In addition to this, slots are allocated by cluster head to all member nodes within a cluster on the basis of their remaining energy so that nodes can switch to sleep mode. Further, to reduce the consumption of energy, data aggregation is also used on the basis of the remaining energy of the cluster head. The performance of proposed CEC technique is evaluated and compared with existing techniques such as SOEECP, LCM and EEPCA. Experimental results show that CEC performs better than existing techniques in measures of the lifetime of the network, consumption of energy, the number of data packets received and accuracy of aggregated data along with the statistical analysis.
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Literature
1.
Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38, 393–422.CrossRef
2.
Abbasi, A. A., & Younis, M. (2007). A survey on clustering algorithms for wireless sensor networks. Computer Communications, 30(14), 2826–2841.CrossRef
3.
Rasyid M. U. H. Al, Nadhori I. U., Sudarsono A., & Luberski R. (2014). Analysis of slotted and unslotted CSMA/CA Wireless Sensor Network for E-healthcare system In Proceedings of the International Conference on Computer, Control, Informatics and Its Applications (IC3INA), Indonesia, 21-23 October.
4.
Wei C., Yang J., Gao Y., & Zhang Z. (2011). Cluster-based routing protocols in wireless sensor networks: A survey, In Proceedings of the International Conference on Computer Science and Network Technology (ICCSNT), Harbin, China, 24-26 December.
5.
Heinzelman W. R., Chandrakasan A. P., & Balakrishnan H. (2000). Energy efficient communication protocol for wireless micro sensor networks, In Proceedings of the 33rd Hawaii International Conference on System Sciences, Island of Maui, January 4-7.
6.
Tripathi M., Gaur M. S., Laxmi V., & Battula R. B. (2013). Energy efficient LEACH-C protocol for Wireless Sensor Network In Proceedings of the Third International Conference on Computational Intelligence and Information Technology, Mumbai, India, Oct 18-19.
7.
Heinzelman, W. R., Chandrakasan, A. P., & Balakrishnan, H. (2002). 2002 Application-SPECIfiC PROTOCOL ARCHITECTURE FOR WIRELESS MICROSENSOR NEtworks. IEEE Transactions on Wireless Communications, 1, 660–670.CrossRef
8.
Tuah, N., Ismail, M., & Jumari, K. (2012). Energy-efficient Improvement for heterogeneous wireless sensor networks. Information Technology Journal, 11, 1687–1695.CrossRef
9.
Mao Ye C.L. G. C., & Wu, J. (2005). EECS: An energy efficient clustering scheme in wireless sensor networks. In Proceedings of the Performance, Computing, and Communications Conference (IPCCC 2005); Phoenix, AZ, USA. 7–9 April 2005; pp. 535–540.
10.
Li, C., Ye, M., Chen, G., & Wu, J. (2005). An energy-efficient unequal clustering mechanism for wireless sensor networks. In Proceedings of the IEEE International Conference on Mobile Ad Hoc and Sensor Systems. Washington, DC, USA. 7–10 November, pp. 8604.
11.
Xiang, X., Lin, C., & Chen, X. (2014). Energy-efficient link selection and transmission scheduling in mobile cloud computing. IEEE Wireless Communication Letters., 3, 153–156.CrossRef
12.
Qiang, Y., Pei, B., Wei, W., & Li, Y. (2015). An efficient cluster head selection approach for collaborative data processing in wireless sensor networks. International Journal of Distributed Sensor Networks, 2015, 1–9.
13.
Younis, O., & Fahmy, S. (2004). HEED: A hybrid, energy-efficient, distributed clustering approach for Ad Hoc sensor networks. IEEE Transaction Mobile Computing, 3, 366–379.CrossRef
14.
Chaudhuri, A., Neogy, S., & Bhaumik, B. B. (2013). Multi-hop unequal clustering routing for wireless sensor networks In: Emerging Research in Computing, Information, Communication and Applications, Elsevier Publications, 2013, Bangalore, India.
15.
Banerjee, S., & Khuller, S. (2001). A clustering scheme for hierarchical control in multi-hop wireless networks. In Proceedings of the Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies; Anchorage, AK, USA. 22–26 April, pp. 1028–1037.
16.
Chan, H., & Perrig, A. (2004). ACE: An emergent algorithm for highly uniform cluster formation. Lecture Notes Computer Science, 2004(2920), 154–171.CrossRef
17.
Smaragdakis, G., Matta, I., & Bestavros, A. (2004) SEP: A stable election protocol for clustered heterogeneous wireless sensor networks. In Proceedings of the Second International Workshop on Sensor and Actor Network Protocols and Applications, Boston, MA, USA, 22–24 August.
18.
Zhu, Q., Wang, M., & Qing, L. (2006). Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks. Computer Communications, 12, 2230–2237.
19.
Elbhiri, Brahim. (2010). Rachid Saadane and Sanaa El fldhi Developed Distributed Energy-Efficient Clustering (DDEEC) for heterogeneous wireless sensor networks, 5th International Symposium on Communications and Mobile Network (ISVC). Morocco: Rabat.
20.
Javaid, N., Qureshi, T. N., Khan, A. H., Iqbal, A., Akhtar, E., & Ishfaq, M. (2013). EDDEEC: Enhanced developed distributed energy-efficient clustering for heterogeneous wireless sensor networks. In Proceedings of the 4th International Conference on Ambient Systems, Networks and Technologies (ANT 2013), Halifax, Nova Scotia, Canada.
21.
22.
Wang, S.-S., & Chen, Z.-P. (2013). Link-aware clustering mechanism LCM: A link-aware clustering mechanism for energy-efficient routing in wireless sensor networks. IEEE Sensors Journal, 13(2), 728–736.CrossRef
23.
Kim, K. T., & Youn, H. Y. (2014). A stochastic and optimized energy efficient clustering protocol for wireless sensor networks. International Journal of Distributed Sensor Networks, 2014, 1–12.
24.
Peng, J., Liu, T., Li, H., & Guo, B. (2013). Energy-efficient prediction clustering algorithm for multilevel heterogeneous wireless sensor networks. International Journal of Distributed Sensor Networks, 9(2), 678214.CrossRef
25.
Yang, D., Li, X., Sawhney, R., & Wang, X. (2009). Geographic and energy-aware routing in wireless sensor networks. International Journal of Ad-Hoc and Ubiquitous Computing, 4(2), 61–70.CrossRef
26.
Zytoune, Fakhri Y., & Aboutajdine, D. (2010). Lifetime maximization algorithm in wireless sensor network. International Journal of Ad Hoc Ubiquitous Computing, 6(3), 140–149.CrossRef
27.
28.
Kong, J., Kim, J., & Eom, D. (2014). Energy-aware distributed clustering algorithm for improving network performance in WSNs. International Journal of Distributed Sensor Networks, 10(2014), 670962.CrossRef
29.
Liao, Y., Qi, H., & Li, W. (2013). Load-balanced clustering algorithm with distributed self-organization for wireless sensor networks. IEEE Sensors, 13(5), 1498–1506.CrossRef
30.
Ye, W., Heidemann, J., & Estrin, D. (2002). An energy-efficient MAC protocol for wireless sensor networks. In Proceedings of the IEEE Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies; New York, USA. 23–24 June, pp. 1567–1576.
31.
Ramanathan, N., Yarvis, M., Chhabra, J., Kushalnagar, N., Krishnamurthy, L., & Estrin, D. (2005) A stream-oriented power management protocol for low duty cycle sensor network applications. In Proceedings of the Second IEEE Workshop on Embedded Networked Sensors, Sydney, Australia. 30–31 May, pp. 53–62.
32.
El-Hoiydi, A., & Decotignie, J. D. (2005). Low power down link MAC protocols for infrastructure wireless sensor networks. Mobile Networking Applications, 10, 675–690.CrossRef
33.
Buettner, M., Yee, G. V., Anderson, E., & Han, R. (2006) X-MAC: A short preamble MAC protocol for duty-cycled wireless sensor networks. In: Proceedings of the 4th International Conference on Embedded Networked Sensor Systems (SenSys’06). Boulder, CO, USA. 31 October–3 November, pp. 307–320.
34.
El-Hoiydi, A. (2002). Aloha with preamble sampling for sporadic traffic in ad hoc wireless sensor networks. In Proceedings of the 2002 IEEE International Conference on Communications; New York, NY, USA. 28 April–2 May, pp. 3418–3423.
35.
Van Dam, T., & Langendoen, K. (2003). An adaptive energy-efficient MAC protocol for wireless sensor networks. In Proceedings of the 1st International Conference on Embedded Networked Sensor Systems (SenSys’03.) Los Angeles, CA, USA. 5–7 November, pp. 171–180.
36.
Yang, S. H., Tseng, H. W., Wu, E. K. & Chen, G. H. (2005). Utilization based duty cycle tuning MAC protocol for wireless sensor networks. In Proceedings of the 2005 IEEE Global Telecommunications Conference, St. Louis, MO, USA. 28 November–2 December, pp. 3255–3262.
37.
Shanti, C., & Sahoo, A. (2010). DGRAM: A delay guaranteed routing and MAC protocol for wireless sensor networks. IEEE Transactions on Mobile Computing, 9, 1407–1423.CrossRef
38.
Chen, Y. S., & Lin, Y. W. C-MAC: An energy-efficient MAC scheme using Chinese–Remainder–Theorem for wireless sensor networks. In Proceedings of the IEEE. International Conference on Communications, Glasgow, UK. 24–28 June 2007; pp. 3576–3581.
39.
Gong, H., Liu, M., Yu, L., & Wang, X. (2009). An event driven TDMA protocol for wireless sensor networks. In Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing, Kunming, China. 6–8 January 2009; pp. 132–136.
40.
Wu, D., Wang, G. Y., & Li X. L. (2010). Distributed TDMA scheduling protocol based on conflict-free for wireless sensor networks. In: Proceedings of the 2010 International Conference on Intelligent Computing and Integrated Systems (ICISS), Guilin, China. 22–24 October, pp. 876–879.
41.
Madden, S., Franklin, M. J., Hellerstein, J. M., & Hong, W. (2002). TAG: A tiny aggregation service for Ad hoc sensor networks. ACM SIGOPS Operating Systems Review, 36, 131–146.CrossRef
42.
Cho, C. Y., Lin, C. L., Hsiao, Y. H., Wang, J. S., & Yang, K. C. (2010). Data aggregation with spatially correlated grouping technique on cluster-based WSNs. In Proceedings of the 2010 Fourth International Conference on Sensor Technologies and Applications (SENSORCOMM), Venice, Italy. 18–25 July. pp. 584–589.
43.
Chen, H., Mineno, H., & Mizuno, T. (2008). Adaptive data aggregation scheme in clustered wireless sensor networks. Computer Communications, 31, 3579–3585.CrossRef
44.
Chen, Z., Yang, S., Li, L., & Xie, Z. (2010). A clustering approximation mechanism based on data spatial correlation in wireless sensor networks. In Proceedings of the 2010 Wireless Telecommunications Symposium (WTS). Tampa, FL, USA. 21–23 April, pp. 1–7.
45.
Bhardwaj, M., Garnett, T., Chandrakasan, A. P. (2001). Upper bounds on the lifetime of sensor networks. In Proceedings of the IEEE International Conference on Communications, Helsinki, Finland, 11–14 June.
46.
Yin, B., Hongchi, S., Shang, Y., Yin, B., Shi, H., & Shang, Y. (2007) Analysis of energy consumption in clustered wireless sensor networks. In Proceedings of the 2nd International Symposium on in Wireless Pervasive Computing, San Juan, Puerto Rico, 5–7 February.
Metadata
Title
Cross-Layer Energy Based Clustering Technique for Heterogeneous Wireless Sensor Networks
Authors
Sukhchandan Randhawa
Sushma Jain
Publication date
15-05-2020
Publisher
Springer US
Published in
Wireless Personal Communications / Issue 2/2020
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-020-07416-w

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