Wang J.,Northwest University, China |
Wang J.,IOT Application Engineering Laboratory of Culture Heritage Conservation |
Fang D.,Northwest University, China |
Fang D.,IOT Application Engineering Laboratory of Culture Heritage Conservation |
And 7 more authors.
Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University | Year: 2012
The heritage monitoring data structure with features of monotony, large redundancy and high tolerance. These features make data compression of the wireless sensor network (WSN) in the existing algorithms a high computational complexity and great computational energy consumption. In this paper the improved Swing Door Trending (SDT) algorithm is applied to the compression of WSN for heritage monitoring. In the case of a large-scale heritage monitor, we analyse the relationship between data compression and network energy consumption. Experiments show that the improved SDT's calculational energy consumption is less then 73% compared with the DWC. And when the compression ratio is less than 25%, the improved compression algorithm SDT can be comparable with the DWC. Under the long-term, large-scale heritage monitor the improved SDT algorithm Data compression is more suitable for WSN.