QAAC: Quality-Assured Adaptive Data Compression for Sensor Data
Aseel Basheer, Kewei Sha · 2016
Wireless sensor networks are widely applied in data collection applications. Energy efficiency is one of the most important design goals. In this paper, we propose QAAC, Quality-Assured Adaptive data Compression, to reduce the amount of data communication so that to save energy. QAAC first builds clusters from dataset using an adaptive clustering algorithm; then a code for each cluster is generated and stored in a Huffman encoding tree, which is used to encode the original dataset in an encoding algorithm with improvement approach. After the encoded data, the Huffman encoding tree and parameters used in the improvement algorithm have been received at the sink, a decompression algorithm is used to retrieve the approximation of the original dataset. The performance evaluation shows that QAAC is efficient and achieves much higher compression ratio than compared lossy and lossless compression algorithms and much less information loss than compared lossy compression algorithms.