Resource-Efficient Floating-Point Data Compression Using MAS in WSN

In a wide range of applications, large amounts of floating-point data are generated by Wireless Sensor Networks (WSNs). This data is often transferred between several sensor nodes, in a multi-hop fashion, before reaching its ultimate destination (the base station). It is well known that data communications is the most energy-consuming task in sensor nodes [1]. This can be a great concern when the nodes are constrained in energy. Therefore, the amount of data to be transferred between nodes should be reduced to save energy. In this paper, we investigate data compression for resource-constraint WSNs; we introduce MAS as a novel adaptive lossless floating-point data compression algorithm for WSNs. MAS exploits the disproportionality in energy consumption between data transmission and processing. Simulation results, obtained from OMNeT++ and Atmel Studio, show that MAS surpasses other tested compression algorithms in terms of compression ratio, compression speed, memory requirements and most importantly energy savings