Title :
A data compression technique for sensor networks with dynamic bandwidth allocation
Author :
Lin, Song ; Gunopulos, Dimitrios ; Kalogeraki, Vana ; Lonardi, Stefano
Author_Institution :
Dept. of Comput. Sci. & Eng., California Univ., Riverside, CA, USA
Abstract :
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.
Keywords :
bandwidth allocation; codes; vector quantisation; wireless sensor networks; codebook updates; communication bandwidth; data compression; dynamic bandwidth allocation; historical information compression; learning vector quantization; sensor data transmission; sensor network; Acoustic sensors; Bandwidth; Channel allocation; Communication channels; Data compression; Sensor arrays; Sensor phenomena and characterization; Temperature sensors; Vector quantization; Wireless sensor networks;
Conference_Titel :
Temporal Representation and Reasoning, 2005. TIME 2005. 12th International Symposium on
Print_ISBN :
0-7695-2370-6
DOI :
10.1109/TIME.2005.6
