Keywords:-
Article Content:-
Abstract
The wireless sensor network is formed by a countless of sensor nodes with communication and
computation abilities. The sensor nodes will lose adequacy with the decrease on energy capacity of
batteries. Effective reduction and adjusting of energy consumption of various sensor nodes play
significant roles in increasing the life cycle of the network and improving the network stability. A
dual cluster head based wireless sensor network routing algorithm is proposed aiming at the
premature death of the cluster head due to very fast energy consumption and the unbalanced energy
consumption of nodes. Firstly, the master cluster heads and the member nodes of the cluster are
determined based on the Enhanced routing algorithm. Secondly, the vice cluster head is selected
from cluster member nodes according to energy consumed by all the member nodes to complete a
process of data transmission, collection and fusion based on the principle of minimum energy
consumption. Any member node in the cluster transmits the data to the cluster head near to it. Both
the master cluster head and the vice cluster head collect and integrate the data, which effectively
reduces and balances the energy consumption of nodes. Based on the simulation results, compared
with the enhanced routing algorithm, the algorithm proposed in this research significantly delays the
death time of the first node in the wireless sensor network, growing the life cycle of the network.
References:-
References
Balanced Clustering Routing Protocol for
WSN," Chinese Journal of Sensors and
Actuators, vol. 26, Mar. 2013, pp. 396-401.
2. G. Lei, W.X Wang, B.X. Sun and S.X. Zheng,
"Experiment on Wireless Sensors Network
based on Double Cluster Head Clustering
Routing Algorithm of Energy Heterogeneous
in Paddy Field," Transactions of the Chinese
Society of Agricultural Engineering, vol. 29,
Dec. 2013, pp. 139146.
3. J.S. Su, W.Z. Guo, c.1. Yu and G.L. Chen,
"Fault-Tolerance Clustering Algorithm with
Load-Balance Aware in Wireless Sensor
Network,"Chinese Journal of Computers, vol.
17, Feb. 2014, pp. 445-456.
4. J.J. Xu, BX Xu, XH. Zhang and Z.X. Sun,
"Improved Minimum Weighted Clustering
Algorithm in Wireless Sensor Networks,"
Journal of Nanjing University of Posts and
Telecommunications (Natural Science Edition),
vol. 36, Oct. 2016, pp. 56-63.
5. C.S. Zhang, J. Xing and S.Q. Zhao, "Energyefficient
Uneven Clustering Algorithm,
"Computer Engineering and Applications, vol.
52, Jul. 2016, pp.106-109.
6. T. Lv, Q.X Zhu, and Y.Y. Zhu, "Energybalanced
Adaptive Clustering Algorithm for
Wireless Sensor Network," Journal of
Computer Applications, vol. 32, Nov. 2012, pp.
3107-3111.
7. J.J. Xu, B.X. Xu, xu. Zhang and ZX Sun,
"Survey of Clustering Algorithms for Wireless
Sensor Networks," Computer Science, vol. 44,
Feb. 2017, pp. 31-37.
8. L. Lin and 1.H. Zhang, "Energy Efficient
Algorithm of Adaptive Clustering for Wireless
Sensor Networks," Instrument Technique and
Sensor, vol. 47, Mar. 2017, pp. 121-126.
9. Qing Li, Zhu Qingxin, Wang Mingwen. "A
distributed energy efficient clustering algorithm for
heterogeneous wireless sensor networks,"
Journal of Software, vol. 1 7, no, 3, pp, 48 1 -
489, 2006.
10. Bo Shen, Shiyong Zhang, Yiping Zhong,
"Cluster-Based Routing Protocols for Wireless
Sensor Networks," Journal of Software, vol.
17, no. 7, pp. 1 588- 1600, 2006.