無線傳感器網(wǎng)絡(luò)中基于序列相關(guān)性的數(shù)據(jù)壓縮算法

翟雙; 錢志鴻; 劉曉慧; 孫大洋

doi:10.11999/JEIT150280

無線傳感器網(wǎng)絡(luò)中基于序列相關(guān)性的數(shù)據(jù)壓縮算法

doi: 10.11999/JEIT150280 cstr: 32379.14.JEIT150280

2.
(吉林大學(xué)通信工程學(xué)院長(zhǎng)春 130012) ②(長(zhǎng)春工業(yè)大學(xué)計(jì)算機(jī)科學(xué)與工程學(xué)院長(zhǎng)春 130012)

基金項(xiàng)目:

國(guó)家自然科學(xué)基金(61371092)

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出版歷程
- 收稿日期: 2015-03-09
- 修回日期: 2016-01-06
- 刊出日期: 2016-03-19

Data Compression Algorithm Based on Sequence Correlation for WSN

2.
(College of Communication Engineering, University of Jilin, Changchun 130012, China)

Funds:

The National Natural Science Foundation of China (61371092)

摘要

摘要: 無線傳感器網(wǎng)絡(luò)(WSN)中傳輸?shù)臄?shù)據(jù)具有相關(guān)性和冗余性。如何有效降低網(wǎng)絡(luò)中的數(shù)據(jù)量，延長(zhǎng)網(wǎng)絡(luò)生命周期，始終是WSN的研究熱點(diǎn)之一。該文基于WSN中數(shù)據(jù)序列的相關(guān)性，提出一種兩步數(shù)據(jù)壓縮算法(TSC-SC)。網(wǎng)絡(luò)中的簇首和簇內(nèi)節(jié)點(diǎn)執(zhí)行各自的壓縮算法：簇首首先執(zhí)行相關(guān)性分組算法，將數(shù)據(jù)分組，減少簇內(nèi)節(jié)點(diǎn)的計(jì)算量以及消除簇內(nèi)數(shù)據(jù)的空間相關(guān)性；簇內(nèi)節(jié)點(diǎn)對(duì)多屬性數(shù)據(jù)分類壓縮，并將壓縮參數(shù)傳至簇首，簇首解壓后再次進(jìn)行分類壓縮，進(jìn)一步消除數(shù)據(jù)相關(guān)性，減少節(jié)點(diǎn)數(shù)據(jù)冗余度，降低通信能耗。為實(shí)現(xiàn)對(duì)壓縮算法的綜合性能評(píng)價(jià)，考慮基本的壓縮要求和算法的計(jì)算能耗，提出了基于能量判別的算法評(píng)估模型(NCER)。仿真結(jié)果表明TSC-SC算法可以有效降低壓縮比和壓縮誤差，充分減少數(shù)據(jù)傳輸量和網(wǎng)絡(luò)的通信能耗，利用NCER指標(biāo)能夠直觀地評(píng)價(jià)算法的性能。
- 無線傳感器網(wǎng)絡(luò) /
- 數(shù)據(jù)壓縮 /
- 序列相關(guān)性
Abstract: The data has correlations and redundancy in Wireless Sensor Network (WSN). How to reduce effectively the amount of communication data and extend the network life cycle is one of researching hot points. The Two-Step data Compression algorithm based on Sequence Correlation (TSC-SC) for WSN is proposed in this paper. The cluster head and the nodes in clusters perform different compression algorithms for themselves. In order to eliminate the spatial correlation of data and reduce the calculated amount, the cluster head nodes perform the grouping algorithm firstly, then the nodes in clusters perform the classifing compression to eliminate correlation for multi-attribute data, and pass the compression parameters to the cluster head; the cluster head perform the classifing compression again after decompressing the parameters. So the data-redundancy and communication energy consumption is further reduced. A new evaluation model named Network Compression Energy Ratio (NCER) based on energy discrimination is also proposed. The evaluation model realizes comprehensive evaluation of compression algorithms by considering both the basic requirements of compression and calculated energy consumption in the nodes. Simulation results show that TSC-SC algorithm can reduce the compression ratio and compression error effectively; the amount of communication data and energy consumption can achieve a satisfactory level in the network. The algorithm can be estimated directly using NCER.
- Wireless Sensor Network (WSN) /
- Data compression /
- Sequence correlation

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