An Ultra-Low Power Data Aggregation System for Wireless Micro Sensor Networks

The paper introduced a novel methodology, for reducing energetic consumption, during data compression in homogenous sensor nodes organized in a cluster based network. Our approach employed a bit-wise operator previously used in the context of the reduction of dynamic energy in external buses. The document defined the compression and decompression laws based on this operator, in a conceptual way much similar to the code division multiple access (CDMA) systems, used in the telecommunication scenario. Each sensor has internally associated a digital signature, used in the compression stage. The host computer tries to recover the original waveform executing the cited operator and applying the inverse signature. The original data has been corrupted by an interference process, which depends on the presence of the other users in the same cluster. The host computer is able to select the best signatures, mostly reducing the energy of the interfering process. Simulations conducted with Matlab and SimplePower indicated our approach gains an 85% in energy consumption compared to the simpler algorithm up to now known (Least Mean Squares). Moreover, simulations verified the host has the capability to recover the transmitted waveforms in