Internet of Things Sensor Node Information Scheduling Model and Energy Saving Strategy

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According to energy constraint problem of wireless sensor node in the Internet of Things (IoT) perception layer, this paper proposed sensor information scheduling model based on mixed logical dynamic (MLD) model and energy saving strategy. First, the amount of transmission data control and the energy consumption of wireless communication control were modeled by MLD mode. Secondly, under MLD model, the sensor node communication scheduler was designed, and reliable scheduling strategy and rules were established for sensor node in different scene, which can adopt different strategy according to the change of scene. Finally, the simulation results show that the sensor node information scheduling model and energy saving strategy can reduce the sensor node data traffic and save more than 50% energy consumption, and the overall data error is 0.018. So it can save the energy consumption of sensor node and guarantee data precision.

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215-220

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September 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Atzori Luigi, Iera Antonio, Morabito Giacomo: The Internet of Things: A survey. COMPUTER NETWORKS Vol. 54 (2010), pp.2787-2805.

DOI: 10.1016/j.comnet.2010.05.010

Google Scholar

[2] Miorandi Daniele, Sicari Sabrina, et. al: Internet of things: Vision, applications and research challenges. AD HOC NETWORKS Vol. 10 (2012), pp.1497-1516.

DOI: 10.1016/j.adhoc.2012.02.016

Google Scholar

[3] Zhikui Chen, Haozhe Wang, Yang Liu, Fanyu Bu, Zhe Wei, A context-aware routing protocol on internet of things based on sea computing model. Journal of Computers Vol. 7 (2012), pp.96-105.

DOI: 10.4304/jcp.7.1.96-105

Google Scholar

[4] Lifang Ge: Incorporating Potential Energy Filed into Efficient Routing in Wireless Microsensor Networks. International Journal of Digital Content Technology and its Applications Vol. 5 (2011), pp.339-345.

DOI: 10.4156/jdcta.vol5.issue10.40

Google Scholar

[5] Qu Liguo, Chai Jingkun, Huang Yourui, Power Control Algorithm of Internet-of-Things Node Based on Vague Set. In Proceedings of 2010 International Symposium on Information Science and Engineering (2010).

DOI: 10.1109/isise.2010.90

Google Scholar

[6] Gao Zhigang, Wu Yifan, Dai Guojun, Xia Haixia, Energy-Efficient Scheduling for Hybrid Tasks in Control Devices for the Internet of Things. SENSORS Vol. 12 (2012), pp.11334-11359.

DOI: 10.3390/s120811334

Google Scholar

[7] Lin Wei, Zhu Qilong, Wireless sensor network data fusion algorithm energy-saving. Journal of Harbin engineering university Vol. 32 (2011), pp.1386-1390.

Google Scholar

[8] Jiping Xiong, Lifeng Xuan, Tao Huang, Jian Zhao: Novel Covert Data Channel in Wireless Sensor Networks Using Compressive Sensing. Journal of Networks Vol. 7(2012), pp.1523-1529.

DOI: 10.4304/jnw.7.10.1523-1529

Google Scholar

[9] Anastasi Giuseppe, Conti Marco, Di Francesco, Mario, etc. Energy conservation in wireless sensor networks: A survey. AD HOC NETWORKS Vol. 7 (2009) pp.537-568.

DOI: 10.1016/j.adhoc.2008.06.003

Google Scholar

[10] Intel Lab Data, http: /db. csail. mit. edu/labdata/ labdata. html.

Google Scholar