article

An efficient cluster-based communication protocol for wireless sensor networks

Authors:

Irfan AwanAuthors Info & Claims

Telecommunications Systems, Volume 55, Issue 3

Pages 387 - 401

https://doi.org/10.1007/s11235-013-9794-y

Published: 01 March 2014 Publication History

Abstract

A wireless sensor network is a network of large numbers of sensor nodes, where each sensor node is a tiny device that is equipped with a processing, sensing subsystem and a communication subsystem. The critical issue in wireless sensor networks is how to gather sensed data in an energy-efficient way, so that the network lifetime can be extended. The design of protocols for such wireless sensor networks has to be energy-aware in order to extend the lifetime of the network because it is difficult to recharge sensor node batteries. We propose a protocol to form clusters, select cluster heads, select cluster senders and determine appropriate routings in order to reduce overall energy consumption and enhance the network lifetime. Our clustering protocol is called an Efficient Cluster-Based Communication Protocol (ECOMP) for Wireless Sensor Networks. In ECOMP, each sensor node consumes a small amount of transmitting energy in order to reach the neighbour sensor node in the bidirectional ring, and the cluster heads do not need to receive any sensed data from member nodes. The simulation results show that ECOMP significantly minimises energy consumption of sensor nodes and extends the network lifetime, compared with existing clustering protocol.

References

[1]

Abbasi, A., & Younis, M. (2007). A survey on clustering algorithms for wireless sensor networks. Computer Communications, 30, 2826---2841.

Digital Library

[2]

Akkaya, K., & Younis, M. (2005). A survey on routing protocols for wireless sensor networks. Ad Hoc Networks, 3(3), 325---349.

[3]

Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). A survey on sensor networks. IEEE Communications Magazine, 40(8), 102---114.

Digital Library

[4]

Al-Karaki, J., & Kamal, A. (2004). Routing techniques in wireless sensor networks: a survey. IEEE Wireless Communications, 11(6), 6---28.

Digital Library

[5]

Ali, M. S., Dey, T., & Biswas, R. (2008). ALEACH: advanced LEACH routing protocol for wireless microsensor networks. In International conference on electrical and computer engineering, ICECE, 20---22 Dec. 2008 (pp. 909---914).

[6]

Batalin, M. A., & Sukhtame, G. S. (2004). Coverage, exploration and deployment by a mobile robot and communication network. Telecommunication Systems, 26(2), 181---196. Special issue on wireless sensor networks.

Digital Library

[7]

Boukerche, A., Cheng, X., & Linus, J. (2005). A performance evaluation of a novel energy-aware data-centric routing algorithm in wireless sensor networks. Wireless Networks, 11(5), 619---635.

Digital Library

[8]

Boukerche, A., Pazzi, R. W. N., & Borges Araujo, R. (2006). Fault-tolerant wireless sensor network routing protocols for the supervision of context-aware physical environments. Journal of Parallel and Distributed Computing, 66(4), 586---599.

Digital Library

[9]

Chang, R., & Kuo, C. (2006). An energy-efficient routing mechanism for wireless sensor networks. In 20th international conference on advanced information networking and applications, 2006, AINA 2006, 18---20 Apr. 2006 (Vol. 2, p. 5).

[10]

Chen, J., & Yu, F. (2007). A uniformly distributed adaptive clustering hierarchy routing protocol. In IEEE international conference on integration technology, ICIT'07, 20---24 Mar. 2007 (pp. 628---632).

[11]

Ci, S., Guizani, M., & Sharif, H. (2007). Adaptive clustering in wireless sensor networks by mining sensor energy data. Computer Communications, 30, 2968---2975.

Digital Library

[12]

Culler, D., Estrin, D., & Srivastava, M. (2004). Overview of sensor networks. Computer, 37(8), 41---49.

Digital Library

[13]

Fan, X., & Song, Y. (2007). Improvement on LEACH protocol of wireless sensor network. In International conference on sensor technologies and applications, SensorComm, 14---20 Oct. 2007 (pp. 260---264).

[14]

Handy, M. J., Haase, M., & Timmermann, D. (2002). Low energy adaptive clustering hierarchy with deterministic cluster-head selection. In Proceedings 4th international workshop on mobile and wireless communications network (pp. 368---372).

[15]

Heinzelman, W. R., 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, 4---7 Jan. 2000 (Vol. 2, p. 10).

[16]

Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4), 660---670.

Digital Library

[17]

Israr, N., & Awan, I. (2007). Coverage-based intercluster communication for load balancing in wireless sensor networks. In International conference on advanced information networking and applications workshops, AINAW'07, 21---23 May 2007 (Vol. 2, pp. 923---928).

[18]

Israr, N., & Awan, I. (2007). Multihop clustering algorithm for load balancing in wireless sensor networks. International Journal of Simulation: Systems, Science & Technology, 8(1), 13---25.

[19]

Jurdak, R., Ruzzelli, A. G., O'Hare, G. M. P., & Lopes, C. V. (2008). Mote-based underwater sensor networks: opportunities, challenges, and guidelines. Telecommunication Systems, 37, 37---47.

Digital Library

[20]

Lim, H. Y., Kim, S. S., Yeo, H. J., Kim, S. W., & Ahn, K. S. (2007). Maximum energy routing protocol based on strong head in wireless sensor networks. In Sixth international conference on advanced language processing and web information technology, ALPIT, 22---24 Aug. 2007 (pp. 414---419).

Digital Library

[21]

Lindsey, S., & Raghavendra, C. (2002). PEGASIS: power-efficient gathering in sensor information systems. In IEEE aerospace conference proceedings (Vol. 3, pp. 1125---1130).

[22]

Manjeshwar, A., & Agarwal, D. P. (2001). TEEN: a routing protocol for enhanced efficiency in wireless sensor networks. In 15th international parallel and distributed processing symposium (IPDPS'01) (p. 3).

[23]

Manjeshwar, A., & Agarwal, D. P. (2002). APTEEN: a hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks. In Proceedings of the 16th international parallel and distributed processing symposium (pp. 195---202).

[24]

Mhatre, V., & Rosenberg, C. (2004). Homogeneous vs heterogeneous clustered sensor networks: a comparative study. In 2004 IEEE international conference on communications, 20---24 June 2004 (Vol. 6, pp. 3646---3651).

[25]

Muruganathan, S. D., Ma, D. C. F., Bhasin, R. I., & Fapojuwo, A. O. (2005). A centralized energy-efficient routing protocol for wireless sensor networks. IEEE Communications Magazine, 43(3), S8---13.

Digital Library

[26]

Nam, D.-H., & Min, H.-K. (2007). An efficient ad-hoc routing using a hybrid clustering method in a wireless sensor network. In Third IEEE international conference on wireless and mobile computing, networking and communications (WiMob 2007), WIMOB (p. 60).

Digital Library

[27]

OMNET++ simulation environment. http://www.omnetpp.org.

[28]

Qian, Y., Zhou, J., Qian, L., & Chen, K. (2006). Highly scalable multihop clustering algorithm for wireless sensor networks. In 2006 international conference on communications, circuits and systems proceedings, 25---28 June 2006 (Vol. 3, pp. 1527---1531).

[29]

Raghunathan, V., Schurgers, C., Park, S., & Srivastava, M. B. (2002). Energy-aware wireless microsensor networks. IEEE Signal Processing Magazine, 19(2), 40---50.

[30]

Soude, H., & Mehat, J. (2006). Energy-efficient clustering algorithm for wireless sensor networks. In International conference on wireless and mobile communications, ICWMC'06, 29---31 July (p. 7).

[31]

Tashtarian, F., Haghighat, A. T., Honary, M. T., & Shokrzadeh, H. (2007). A new energy-efficient clustering algorithm for wireless sensor networks. In 15th international conference on software, telecommunications and computer networks, SoftCOM 2007, 27---29 Sept. 2007 (pp. 1---6).

[32]

Wang, Y., Yang, T. L. X., & Zhang, D. (2009). An energy-efficient and balance hierarchical unequal clustering algorithm for large scale sensor network. Information Technology Journal, 8(1), 28---38.

[33]

Wu, J., & Li, H. (2001). A dominating-set-based routing scheme in ad hoc wireless networks. Telecommunication Systems, 3, 63---84.

[34]

Younis, O., & Fahmy, S. (2004). Distributed clustering in ad-hoc sensor networks: a hybrid, energy-efficient approach. In Twenty-third annual joint conference of the IEEE computer and communications societies, INFOCOM 2004, 7---11 Mar. 2004 (Vol. 1, p. 640).

[35]

Younis, O., & Fahmy, S. (2004). HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing, 3(4), 366---379.

[36]

Zhang, W., Liang, Z., Hou, Z., & Tan, M. (2007). A power efficient routing protocol for wireless sensor network. In 2007 IEEE international conference on networking, sensing and control, 15---17 Apr. 2007 (pp. 20---25).

[37]

Zhang, Z., Ma, M., & Yang, Y. (2008). Energy-efficient multihop polling in clusters of two-layered heterogeneous sensor networks. IEEE Transactions on Computers, 57(2), 231---245.

Digital Library

[38]

Zhou, Y., Hart, M., Vadgama, S., & Rouz, A. (2007). A hierarchical clustering method in wireless ad hoc sensor networks. In IEEE international conference on communications, ICC'07, 24---28 June 2007 (pp. 3503---3509).

[39]

Zhou, P., Pei, X., & Xu, K. (2007). A semi-centralized approach for optimized multihop virtual MIMO wireless sensor networks. In Second international conference on communications and networking in China, CHINACOM'07, 22---24 Aug. 2007 (pp. 877---881).

Cited By

Yang MGao CHan J(2022)Edge Computing Deployment Algorithm and Sports Training Data Mining Based on Software Defined NetworkComputational Intelligence and Neuroscience10.1155/2022/80563602022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/8056360
Cao XLuo Y(2022)Experimental Research on Span Direction Effect of Vortex-Induced Vibration of Bridge Main Girder Based on Symmetric AlgorithmMobile Information Systems10.1155/2022/54111192022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/5411119
Selvi MSanthosh Kumar SGanapathy SAyyanar AKhanna Nehemiah HKannan A(2021)An Energy Efficient Clustered Gravitational and Fuzzy Based Routing Algorithm in WSNsWireless Personal Communications: An International Journal10.1007/s11277-020-07705-4116:1(61-90)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1007/s11277-020-07705-4
Show More Cited By

An efficient cluster-based communication protocol for wireless sensor networks
1. General and reference
  1. Cross-computing tools and techniques
2. Networks
  1. Network types

Recommendations

Adaptive decentralized re-clustering protocol for wireless sensor networks

Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way since the energy is limited. The ...
Energy efficient constant cluster node scheduling protocol for wireless sensor networks

The Wireless sensor network (WSN) consisting of a large number of sensors are effective for gathering data in a variety of environments. Since the sensors operate on battery of limited power, it is a great challenging aim to design an energy efficient ...
An Energy Efficient Cluster-Head Selection for Wireless Sensor Networks
ISMS '10: Proceedings of the 2010 International Conference on Intelligent Systems, Modelling and Simulation

Recent advances in wireless sensor networks have led to many new protocols specifically designed for sensor networks where energy awareness is an essential consideration. Clustering is a key routing technique used to reduce energy consumption. ...

Comments

Information & Contributors

Information

Published In

cover image Telecommunications Systems

Telecommunications Systems Volume 55, Issue 3

March 2014

114 pages

ISSN:1018-4864

Issue’s Table of Contents

Copyright © Copyright © 2014 Springer Science+Business Media New York.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 March 2014

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

13
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 07 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Yang MGao CHan J(2022)Edge Computing Deployment Algorithm and Sports Training Data Mining Based on Software Defined NetworkComputational Intelligence and Neuroscience10.1155/2022/80563602022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/8056360
Cao XLuo Y(2022)Experimental Research on Span Direction Effect of Vortex-Induced Vibration of Bridge Main Girder Based on Symmetric AlgorithmMobile Information Systems10.1155/2022/54111192022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/5411119
Selvi MSanthosh Kumar SGanapathy SAyyanar AKhanna Nehemiah HKannan A(2021)An Energy Efficient Clustered Gravitational and Fuzzy Based Routing Algorithm in WSNsWireless Personal Communications: An International Journal10.1007/s11277-020-07705-4116:1(61-90)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1007/s11277-020-07705-4
Jain SVenkatadari MShrivastava NJain SVerma R(2021)NHCDRA: a non-uniform hierarchical clustering with dynamic route adjustment for mobile sink based heterogeneous wireless sensor networksWireless Networks10.1007/s11276-021-02585-327:4(2451-2467)Online publication date: 1-May-2021
https://dl.acm.org/doi/10.1007/s11276-021-02585-3
Radhika MSivakumar P(2021)Energy optimized micro genetic algorithm based LEACH protocol for WSNWireless Networks10.1007/s11276-020-02435-827:1(27-40)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1007/s11276-020-02435-8
Zeng MHuang XZheng BFan X(2019)A Heterogeneous Energy Wireless Sensor Network Clustering ProtocolWireless Communications & Mobile Computing10.1155/2019/73672812019Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1155/2019/7367281
Jha SEyong E(2018)An energy optimization in wireless sensor networks by using genetic algorithmTelecommunications Systems10.1007/s11235-017-0324-167:1(113-121)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1007/s11235-017-0324-1
Alphonse PJA Sivaraj C Janakiraman T N. (2017)An Energy-Efficient Layered Clustering Algorithm for Routing in Wireless Sensor NetworksInternational Journal of Distributed Systems and Technologies10.4018/IJDST.20170701038:3(43-66)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.4018/IJDST.2017070103
Selvi MLogambigai RGanapathy SRamesh LNehemiah HArputharaj KAkila VSivakumar NSaruladha KZayaraz GIlavarasan E(2016)Fuzzy Temporal Approach for Energy Efficient Routing in WSNProceedings of the International Conference on Informatics and Analytics10.1145/2980258.2982109(1-5)Online publication date: 25-Aug-2016
https://dl.acm.org/doi/10.1145/2980258.2982109
Yang LLu YZhong YWu XXing S(2016)A hybrid, game theory based, and distributed clustering protocol for wireless sensor networksWireless Networks10.1007/s11276-015-1011-322:3(1007-1021)Online publication date: 1-Apr-2016
https://dl.acm.org/doi/10.1007/s11276-015-1011-3
Show More Cited By

View Options

View options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Issue’s Table of Contents