Bounded Error Data Compression and Aggregation in Wireless Sensor Networks
Date Issued
2011
Date
2011
Author(s)
Li, Meng-Han
Abstract
In this paper, an efficient data compression and aggregation method, called BEDCA, is proposed to reduce the size of transmission data under the given bounded error. We first apply the observed transmission data to construct a codebook which is related to the data correlation of the monitoring environment. Given a bounded error, the proposed method determines whether the new sensed data should be compressed or not by comparing it with the reference data such as the previous sensed data (for temporal correlation), the neighboring sensed data (for spatial correlation), and the codebook encoded data (for data correlation). Thus, the total size of transmission data can be minimized for energy saving. We use a real dataset to evaluate the performance of our mechanism. Even if the bounded error is set as a small value (under 0.5%), the proposed method can reduce a lot of the transmission data (over 70%) to cut down the total energy consumption. Our improvement exceeds 90% in the total energy consumed when bounded error is more than 1%. Compared to VQ, our proposed methods can enhance 20% better compression ratio and save 62% energy at least. Our method improve 38% compression ratio and retain 52% energy at least than DCT. Moreover, in our simplified hierarchy model of architecture, more than 20% energy can be saved in any aggregation function in SN than aggregated in sink. Experiment results show that the proposed method can make WSNs more efficient in energy consumption.
Subjects
wireless sensor networks
bounded error
data compression
query operations
temporal correlation
spatial correlation
data correlation
energy efficiency
Type
thesis
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