Piggery Environmental Control System Based on Wireless Sensor Networks with Energy Optimization

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According to the characteristics of piggery, such as complex environment, numerous control objects, complex wiring, a piggery environment control system based on wireless sensor networks was designed. This system consisted of the wireless network composed of various devices and sensors in piggery, the control center with ARM-LINUX and the remote control center. The energy of sensor nodes was offered by batteries in wireless sensor networks so that the power source was limited. In order to strengthen the node energy management, the LEACH algorithm was combined with AODV routing protocol, and a new optimization algorithm called LEACH-A was proposed in this paper. The wireless sensor networks execution process was divided into two phases, including cluster building and data transmission. In the two phases, the node residual energy was calculated by a weighted function and the cluster head role was changed by the size of remaining energy. NS-2 simulation results show that the proposed algorithm prolonged the lifetime of the nodes and the networks, and realized the energy optimization management.

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865-868

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November 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Liu Zhi, Qiu Zhengding. Wireless sensor network clustering routing algorithm (RBMC) based on jump more than ring[J]. Journal on Communications, 2008, 29(3): 104-113.

Google Scholar

[2] Miu Chongchong, Chen Qingkui, Cao Jianwei, Zhang Gang. Wireless sensor non-uniformclustering routing algorithm based on ant colony optimization algorithm[J]. Computer application, 2013, 33(12): 3410-3414, in Chinese.

DOI: 10.3724/sp.j.1087.2013.03410

Google Scholar

[3] Pratyay Kuilan, Prasanta K. Jana. Energy efficient clustering and Routing algorithms for wireless sensor networks: Particle swarm optimization approach[J]. Engineering Applications ofArtificial Intelligence, 2014, 20(2): 127-140.

DOI: 10.1016/j.engappai.2014.04.009

Google Scholar

[4] Raquel A.F. Minia, Antonio A. F, Energy-efficient design of wireless sensor networks based on finite energy budget[J] Computer Communications, 2012, 23(5): 1736-1748.

DOI: 10.1016/j.comcom.2012.05.009

Google Scholar

[5] Abusaimeh H., Yang S. Energy-aware optimization of the number of clusters and cluster-heads in WSN(C). 2012 International Conference on Innovations in Information Technology, (2012), p.178.

DOI: 10.1109/innovations.2012.6207726

Google Scholar

[6] Abusaimeh H., Yang S. Balance the Power Consumption Speed in Flat and Hierarchical WSN[J]. International Journal of Automation and Computing, 2008 5(4): 366-375.

DOI: 10.1007/s11633-008-0366-7

Google Scholar