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Sensors 2018, 18(9), 3118;

Entropy Correlation and Its Impacts on Data Aggregation in a Wireless Sensor Network

School of Information and Communication Technology, Hanoi University of Science and Technology, 11615 Hanoi, Vietnam
Author to whom correspondence should be addressed.
Received: 30 July 2018 / Revised: 7 September 2018 / Accepted: 13 September 2018 / Published: 15 September 2018
(This article belongs to the Section Sensor Networks)
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A correlation characteristic has significant potential advantages for the development of efficient communication protocols in wireless sensor networks (WSNs). To exploit the correlation in WSNs, the correlation model is required. However, most of the present correlation models are linear and distance-dependent. This paper proposes a general distance-independent entropy correlation model based on the relation between joint entropy and the number of members in a group. This relation is estimated using entropy of individual members and entropy correlation coefficients of member pairs. The proposed model is then applied to evaluate two data aggregation schemes in WSNs including data compression and representative schemes. In the data compression scheme, some main routing strategies are compared and evaluated to find the most appropriate strategy. In the representative scheme, with the desired distortion requirement, a method to calculate the number of representative nodes and the selection of these nodes are proposed. The practical validations showed the effectiveness of the proposed correlation model and data reduction schemes. View Full-Text
Keywords: entropy; correlation; distortion; data compression; representative node entropy; correlation; distortion; data compression; representative node

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Nguyen Thi Thanh, N.; Nguyen Kim, K.; Ngo Hong, S.; Ngo Lam, T. Entropy Correlation and Its Impacts on Data Aggregation in a Wireless Sensor Network. Sensors 2018, 18, 3118.

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