Low-Energy Adaptive Unequal Clustering Protocol Using Fuzzy c-Means in Wireless Sensor Networks

Clustering technique in wireless sensor networks incorporate proper utilization of the limited energy resources of the deployed sensor nodes with the highest residual energy that can be used to gather data and send the information. However, the problem of unbalanced energy consumption exists in a particular cluster node in the network. Some more powerful nodes act as cluster head to control sensor network operation when the network is organized into heterogeneous clusters. It is important to assume that energy consumption of these cluster head nodes is balanced. Often the network is organized into clusters of equal size where cluster head nodes bear unequal loads. Instead in this paper, we proposed a new protocol low-energy adaptive unequal clustering protocol using Fuzzy c-means in wireless sensor networks (LAUCF), an unequal clustering size model for the organization of network based on Fuzzy c-means (FCM) clustering algorithm, which can lead to more uniform energy dissipation among the cluster head nodes, thus increasing network lifetime. A heuristic comparison between our proposed protocol LAUCF and other different energy-aware protocol including low energy adaptive clustering hierarchy (LEACH) has been carried out. Simulation result shows that our proposed heterogeneous clustering approach using FCM protocol is more effective in prolonging the network lifetime compared with LEACH and other protocol for long run.

[1]  Anthony Ephremides,et al.  The Design and Simulation of a Mobile Radio Network with Distributed Control , 1984, IEEE J. Sel. Areas Commun..

[2]  Gregory J. Pottie,et al.  Self-organizing distributed sensor networks , 1999, Defense, Security, and Sensing.

[3]  Wu Min,et al.  BPEC:An Energy-Aware Distributed Clustering Algorithm in WSNs , 2009 .

[4]  Catherine Rosenberg,et al.  Design guidelines for wireless sensor networks: communication, clustering and aggregation , 2004, Ad Hoc Networks.

[5]  Mario Gerla,et al.  Adaptive Clustering for Mobile Wireless Networks , 1997, IEEE J. Sel. Areas Commun..

[6]  Zhong Chen,et al.  LENO: LEast Rotation Near-Optimal Cluster Head Rotation Strategy in Wireless Sensor Networks , 2007, 21st International Conference on Advanced Information Networking and Applications (AINA '07).

[7]  Chen Gui-Hai,et al.  EADEEG:An Energy-Aware Data Gathering Protocol for Wireless Sensor Networks , 2007 .

[8]  Wu Xiao The Energy Hole Problem of Nonuniform Node Distribution in Wireless Sensor Networks , 2008 .

[9]  Timothy J. Shepard A channel access scheme for large dense packet radio networks , 1996, SIGCOMM 1996.

[10]  Gregory J. Pottie,et al.  Wireless integrated network sensors , 2000, Commun. ACM.

[11]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[12]  William J. Kaiser,et al.  Low power signal processing architectures for network microsensors , 1997, Proceedings of 1997 International Symposium on Low Power Electronics and Design.

[13]  Wendi B. Heinzelman,et al.  An analysis of strategies for mitigating the sensor network hot spot problem , 2005, The Second Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services.

[14]  Jonathan R. Agre,et al.  An Integrated Architecture for Cooperative Sensing Networks , 2000, Computer.

[15]  Jie Wu,et al.  An energy-efficient unequal clustering mechanism for wireless sensor networks , 2005, IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005..

[16]  Gregory J. Pottie,et al.  Wireless sensor networks , 1998, 1998 Information Theory Workshop (Cat. No.98EX131).

[17]  Satish Kumar,et al.  Next century challenges: scalable coordination in sensor networks , 1999, MobiCom.

[18]  Yongcai Wang,et al.  Energy-driven adaptive clustering data collection protocol in wireless sensor networks , 2004, 2004 International Conference on Intelligent Mechatronics and Automation, 2004. Proceedings..

[19]  Wendi Heinzelman,et al.  Proceedings of the 33rd Hawaii International Conference on System Sciences- 2000 Energy-Efficient Communication Protocol for Wireless Microsensor Networks , 2022 .

[20]  Li Qing,et al.  Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks , 2006, Comput. Commun..

[21]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[22]  Gürhan Küçük,et al.  Reducing reorder buffer complexity through selective operand caching , 2003, ISLPED '03.

[23]  Wei Wang,et al.  A Fuzzy Based Clustering Protocol for Energy-Efficient Wireless Sensor Networks , 2013 .

[24]  Rajeev Tripathi,et al.  Optimal number of clusters in wireless sensor networks: An FCM approach , 2010 .

[25]  R. Ruppe,et al.  Near Term Digital Radio (NTDR) system , 1997, MILCOM 97 MILCOM 97 Proceedings.

[26]  Deborah Estrin,et al.  Directed diffusion: a scalable and robust communication paradigm for sensor networks , 2000, MobiCom '00.

[27]  W. Rabiner,et al.  Design considerations for distributed microsensor systems , 1999, Proceedings of the IEEE 1999 Custom Integrated Circuits Conference (Cat. No.99CH36327).

[28]  Matthew Ettus,et al.  System capacity, latency, and power consumption in multihop-routed SS-CDMA wireless networks , 1998, Proceedings RAWCON 98. 1998 IEEE Radio and Wireless Conference (Cat. No.98EX194).

[29]  Ossama Younis,et al.  HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks , 2004, IEEE Transactions on Mobile Computing.

[30]  Adnan Yazici,et al.  An energy aware fuzzy approach to unequal clustering in wireless sensor networks , 2013, Appl. Soft Comput..