An energy-efficient SD-based LZW algorithm in dynamic wireless sensor networks

Minimizing the energy consumption in both circuit components and RF signal transmission is a crucial challenge in the design of a Wireless Sensor Network (WSN). Toward this goal, we present an energy-efficient protocol for the physical layer of the IEEE 802.15.4 standard that deploys the green modulation and Raptor coding in a realistic channel model inspired by the Gilbert-Elliott channel. To save the energy more efficiently and motivated by the fact that data processing in WSNs consumes much less power than the data transmission, we propose an efficient LZW-based compression scheme namely the Sifted Dictionary-based LZW (SD-LZW) using the probability of occurrence of all strings appeared in output data stream. The proposed data compression scheme is capable of adjusting to any type of data input and of returning output using the best possible compression ratio. It is shown numerically that the SD-LZW outperforms two specifically designed compression algorithms for WSNs in various channel realizations, in particular, when the sensor node makes sequential position changes. The SD-LZW algorithm requires very low computational power, compresses data on the fly and uses a very small dictionary whose optimal size is determined by selecting the specific metric known as τ_opt.