The Neural Network based Technique for Fault Tolerance in Wireless Sensor Networks
Keywords:
WSN, Neural Networks, Boltzmann learningAbstract
Wireless sensor network is the self-configuring network where any sensor node can join or leave the network when they want. In Wireless sensor network no central controller is present. Wireless sensor nodes are responsible for data routing in the network. Wireless Sensor nodes are very small in size and have limited resources. In such far places it is very difficult to recharge or replace the battery of the sensor nodes. In such conditions, we focus to reduce the battery consumption of the sensor nodes. In this work, a new technique is proposed to reduce battery consumption. It will be based on the dynamic clustering using neural network. Before data transmission sensor nodes form the cluster dynamically using Boltzmann learning of the neural network and weights are adjust according to the situation and it also enhance the efficiency of the dynamic clustering. Experimental results show that new proposed technique is more efficient, reliable and provide more throughput as compare to the existing technique.
References
- Isaac, S. J., Hancke, G. P., Madhoo, H., & Khatri, A., "A survey of wireless sensor network applications from a power utility's distribution perspective",2011, IEEE, AFRICON, (pp. 1-5)
- Maraiya, K., Kant, K., & Gupta, N., "Application based study on wireless sensor network", 2011, International Journal of Computer Applications (0975–8887) Volume, 21, 9-15
- Sharma, P., & Rai, M. K., "Review Paper on Cluster Based Caching Technique for Wireless Sensor Networks with multi-sink", 2013, International Journal for Advance Research in Engineering and Technology, 1(2), 23
- Dimokas, N., Katsaros, D., & Manolopoulos, Y., "Cooperative caching in wireless multimedia sensor networks", 2008, Mobile Networks and Applications, 13(3-4), 337-356
- Li, X., Nayak, A., & Stojmenovic, I., "Sink mobility in wireless sensor networks", 2010, Wireless sensor and actuator networks, 153
- Pant, S., Chauhan, N., & Kumar, P., "Effective cache based policies in wireless sensor networks: A survey", 2010, International Journal of Computer Applications (0975–8887) Volume, 11, 17-21
- Bakr, B. A., & Lilien, L., "A quantitative comparison of energy consumption and WSN lifetime for LEACH and LEACH-SM", 2011, Distributed Computing Systems Workshops (ICDCSW), 31st International Conference on (pp. 182-191), IEEE
- Nikodem, M., & Wojciechowski, B., "Upper Bounds on Network Lifetime for Clustered Wireless Sensor Networks", 2011, IEEE, New Technologies, Mobility and Security (NTMS), 4th IFIP International Conference on (pp. 1-6)
- Jiang, L., Bing Fang, & Li., "Energy optimized approach based on clustering routing protocol for wireless sensor networks", 2013, CCD Conference, IEEE
- Wang, Y., & Guo, S., "Optimized energy-latency cooperative transmission in duty-cycled wireless sensor networks", 2013,IEEE, Mechatronics and Automation (ICMA), International Conference on (pp. 185-190)
- Zhang, D., Li, G., Zheng, K., Ming, X., & Pan, Z. H.,"An Energy-Balanced Routing Method Based on Forward-Aware Factor for Wireless Sensor Networks",2014, Industrial Informatics, IEEE Transactions on, 10(1), 766-773
- Gouvy, N., Hamouda, E., Mitton, N., & Zorbas, D., "Energy efficient multi-flow routing in mobile Sensor Networks", 2013, Wireless Communications and Networking Conference (WCNC), 2013 IEEE (pp. 1968-1973), IEEE
Downloads
Published
Issue
Section
License
Copyright (c) IJSRSET

This work is licensed under a Creative Commons Attribution 4.0 International License.