An Efficient and Adaptive Data Compression Technique for Energy Conservation in Wireless Sensor Networks

Wireless sensor networks are superior to wired sensing systems from the economical side provided that the latter require a separate twisted shielded-pair wire connection. Thus, implementation costs for the latter are high. However, wireless sensors have to function for an extensive period of time in order to achieve cost minimization and to successfully complete their particular mission. Therefore, conserving the allocated energy is very important and represents a major dilemma which stands against the wide-spreading of this technology. In this paper, a novel local adaptive data compression based on Fuzzy transform is proposed to minimize the bandwidth, the memory space, and the energy consumed in radio communication. An evaluation of the compression technique is provided. During this evaluation, the proposed technique is examined using real temperature data. The results have shown that the proposed technique can highly reduce the overall power consumption by up to 90 percent. Moreover, a modification of the proposed technique is presented which improves the accuracy of the recovered signal even with high compression ratios.