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Sensors 2017, 17(5), 1107; doi:10.3390/s17051107

Power Allocation Based on Data Classification in Wireless Sensor Networks

1,†
and
1,2,†,*
1
School of Mechanical and Electrical Engineering, China University of Mining & Technology, Xuzhou 221116, China
2
Jiangsu Key Laboratory of Mine Mechanical and Electrical Equipment, China University of Mining & Technology, Xuzhou 221116, China
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: Jaime Lloret Mauri and Guangjie Han
Received: 29 March 2017 / Revised: 8 May 2017 / Accepted: 10 May 2017 / Published: 12 May 2017
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
View Full-Text   |   Download PDF [1780 KB, uploaded 12 May 2017]   |  

Abstract

Limited node energy in wireless sensor networks is a crucial factor which affects the monitoring of equipment operation and working conditions in coal mines. In addition, due to heterogeneous nodes and different data acquisition rates, the number of arriving packets in a queue network can differ, which may lead to some queue lengths reaching the maximum value earlier compared with others. In order to tackle these two problems, an optimal power allocation strategy based on classified data is proposed in this paper. Arriving data is classified into dissimilar classes depending on the number of arriving packets. The problem is formulated as a Lyapunov drift optimization with the objective of minimizing the weight sum of average power consumption and average data class. As a result, a suboptimal distributed algorithm without any knowledge of system statistics is presented. The simulations, conducted in the perfect channel state information (CSI) case and the imperfect CSI case, reveal that the utility can be pushed arbitrarily close to optimal by increasing the parameter V, but with a corresponding growth in the average delay, and that other tunable parameters W and the classification method in the interior of utility function can trade power optimality for increased average data class. The above results show that data in a high class has priorities to be processed than data in a low class, and energy consumption can be minimized in this resource allocation strategy. View Full-Text
Keywords: data classification; power allocation; Lyapunov drift optimization; wireless senor networks; coal mines data classification; power allocation; Lyapunov drift optimization; wireless senor networks; coal mines
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wang, H.; Zhou, G. Power Allocation Based on Data Classification in Wireless Sensor Networks. Sensors 2017, 17, 1107.

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