Aggregated Deflate-RLE compression technique for body sensor network

The future of healthcare delivery systems and tele medical applications will undergo a radical change due to the developments in wearable technologies, medical sensors, mobile computing and communication techniques. E-health was born with the integration of networks and telecommunications when dealing with applications of collecting, sorting and transferring medical data from distant locations for performing remote medical collaborations and diagnosis. Energy requirement is central to many battery-constrained systems, but they are essential in body sensor networks (BSNs) due to energy and resource constraints, and the critical nature of many healthcare applications. On-node signal processing and compression techniques can save energy by greatly reducing the amount of data transmitted over the wireless channel, but lossy techniques can incur a reduction in application. In this paper we are proposing an aggregation of Deflate and RLE algorithm called Aggregated Deflate RLE (ADR). ADR compression algorithm which provides better compression ratio with minimum compression time as compared to other existing compression techniques like LZW, Huffman and Deflate. We provide here various comparative result of our algorithm with above compression techniques which proves that we are providing best technique for compression of body sensor network data.