Optimization of Energy Heterogeneous Cluster-Head Selection in Farmland WSN

Power consumption is a key point of WSN (Wireless Sensor Network) lifespan. Because of difference among monitoring objects and complex signal channel condition, the power consumption of each node in farmland WSN is uneven, which makes the network performing as multi-level energy heterogeneous. LEACH and its improving algorithms average the power consumption between nodes by clustering and cluster-head switching. But the cluster-head voting brings a lot extra power consumption. To solve this problem, this paper proposes EACHS (Energy Approximation Cluster-Head Selection), an optimized cluster-head selection mechanism that approximates the energy of cluster-head targeting the lowest energy level in the network. When approaching the target, the current cluster-head collects the energy status of all nodes and determines which one becoming the new cluster-head. The simulation results show that, EACHS can balance the network power consumption and reduce most protocol cost, prolong the overall network lifespan.

[1]  Deborah Estrin,et al.  Medium access control with coordinated adaptive sleeping for wireless sensor networks , 2004, IEEE/ACM Transactions on Networking.

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

[3]  Xiang Yu Research on Power State Transition Model Wireless Sensor Network Node , 2009 .

[4]  Rajesh Krishnan,et al.  Message-efficient self-organization of wireless sensor networks , 2003, 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003..

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

[6]  S.A. Khan,et al.  Analyzing & Enhancing energy Efficient Communication Protocol for Wireless Micro-sensor Networks , 2005, 2005 International Conference on Information and Communication Technologies.

[7]  QingLi,et al.  Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks , 2006 .

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

[9]  Qilian Liang,et al.  An energy-efficient protocol for wireless sensor networks , 2005, VTC-2005-Fall. 2005 IEEE 62nd Vehicular Technology Conference, 2005..

[10]  Jia Zhi-ping System Design Based on Energy Efficiency in Wireless Sensor Networks , 2010 .

[11]  Dhiraj K. Pradhan,et al.  A cluster-based approach for routing in dynamic networks , 1997, CCRV.

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