An Efficient Sleeping Scheduling for Saving Energy Consumption in Wireless Sensor Networks

Abstract:

Wireless Sensor Networks (WSNs) has been widely recognized as a promising technology in smart grid. However, sensor nodes have limited battery energy. So, we present a mathematical model which is to reduce energy consumption and prolong the lifetime of WSNs. Because of the high density of sensor nodes deployment, a sleep mechanism is proposed to make all sensor nodes work by turns while all service requests can be satisfied. And then, an Improved Sleep Mechanism is put forward to remove redundant active nodes. The simulation result indicates that energy consumption adopting the ISNSS is lower than or equal to the energy consumption adopting SNSS. The SNSS and ISNSS all can save some energy of WSNs to some extent and when the redundant active nodes are removed, the network energy consumption is further reduced based on the SNSS.

• Periodical: Applied Mechanics and Materials (Volumes 229-231)
• Pages: 1261-1264
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.229-231.1261
• Online since: November 2012
• Authors: Li Peng Lu, Ming Yue Zhai, Ying Liu, Xiao Da Sun
• Keywords: Saving Energy Consumption, Sleeping Scheduling, Wireless Sensor Network (WSN), Working by Turns

References

[1] Lu Zhijun, Huan Ruohan and Zhou Zhaoyang. Application Prospects of Internet of Things in Smart Grid[J]. Telecommunications for Electric Power System, (2010), Vol. 31, pp.50-52.

[2] Wang Yangguang, Yin Xinggen and You Dahai. Application of Wireless Sensor Networks in Smart Grid. Power System Technology, May, (2010).

[3] D. Tian and N.D. Georganas. A coverage-preserving node scheduling scheme for large wireless sensor networks. In First ACM International Workshop on Wireless Sensor Networks and Applications, (2002).

DOI: 10.1145/570738.570744

[4] J. Deng, Y.S. Han, W. Heinzelman and P. Varshney. Balanced-energy sleep scheduling scheme for high density cluster-based sensor networks. In The 4th workshop on Applications and Services in Wireless Networks, (2004), pp.99-108.

DOI: 10.1109/aswn.2004.185160

[5] Hai Lid, Pengjun Wan, Chih-Wei Yi, Jia Xiaohua, Sam Makki and Nilci Pissinou. Maximal Lifetime Scheduling in Sensor Surveillance Networks, INFOCOM 2005. 24th Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings IEEE, (2005).

DOI: 10.1109/infcom.2005.1498533

[6] Cheng Shijie, Li Xingyuan, Zhang Zhizhe. Entire-grid-area Information-sharing and Integrated Applications in United Information System for Smart Grid [J]. Proceedings of the CSEE, (2010), Vol. 31, pp.8-14.

[7] Wang Jianping, Li Deying, Xing Guoliang and Du Hongwei. Cross-Layer Sleep Scheduling Design in Service-Oriented Wireless Sensor Networks. IEEE transactions on mobile computing, (2010) Vol. 9, pp.1622-16.

DOI: 10.1109/tmc.2010.124