{"title":"基于Huffman和Lempel-Ziv的无线传感器网络数据压缩算法","authors":"S. Renugadevi, P. S. Nithya Darisini","doi":"10.1109/ICPRIME.2013.6496521","DOIUrl":null,"url":null,"abstract":"In the recent years, wireless sensor networks have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery powered devices, it is essential to minimize the energy consumption of the nodes so that the network lifetime can be extended. Most of the energy is consumed in the processing and transmission of data. Applying compression algorithms on the wireless sensor data prior to transmission is one of the efficient ways to save energy. In this paper we propose data compression algorithms based on Huffman and Lempel-Ziv techniques and compare the efficiency of different algorithms in a wireless sensor network scenario.","PeriodicalId":123210,"journal":{"name":"2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Huffman and Lempel-Ziv based data compression algorithms for wireless sensor networks\",\"authors\":\"S. Renugadevi, P. S. Nithya Darisini\",\"doi\":\"10.1109/ICPRIME.2013.6496521\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the recent years, wireless sensor networks have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery powered devices, it is essential to minimize the energy consumption of the nodes so that the network lifetime can be extended. Most of the energy is consumed in the processing and transmission of data. Applying compression algorithms on the wireless sensor data prior to transmission is one of the efficient ways to save energy. In this paper we propose data compression algorithms based on Huffman and Lempel-Ziv techniques and compare the efficiency of different algorithms in a wireless sensor network scenario.\",\"PeriodicalId\":123210,\"journal\":{\"name\":\"2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPRIME.2013.6496521\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPRIME.2013.6496521","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Huffman and Lempel-Ziv based data compression algorithms for wireless sensor networks
In the recent years, wireless sensor networks have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery powered devices, it is essential to minimize the energy consumption of the nodes so that the network lifetime can be extended. Most of the energy is consumed in the processing and transmission of data. Applying compression algorithms on the wireless sensor data prior to transmission is one of the efficient ways to save energy. In this paper we propose data compression algorithms based on Huffman and Lempel-Ziv techniques and compare the efficiency of different algorithms in a wireless sensor network scenario.