A data compression technique for sensor networks with dynamic bandwidth allocation
Song Lin, Dimitrios Gunopulos, Vana Kalogeraki, Stefano Lonardi · 2005
In this paper, we have presented a new data compression technique, designed for historical information compression in sensor networks. Our method employs the LVQ learning process to construct the codebook and the codebook's updates are compressed to save bandwidth for sensor data transmission. In addition, we have addressed the dynamic bandwidth allocation problem in sensor networks. Our DBA algorithm can dynamically adjust the communication bandwidth of different sensors in order to balance data compression qualities at different sensors.