{"title":"增强LZMA和BZIP2,改进能量数据压缩","authors":"Zaid Bin Tariq, N. Arshad, M. Nabeel","doi":"10.5220/0005454202560263","DOIUrl":null,"url":null,"abstract":"Smart grid is the next generation of electricity production, transmission and distribution system. This is possible through an overlayed communication layer with the power delivery layer. Due to this communication layer smart grids produce enormous amounts of data. This data may be analyzed for improving the quality of service of smart grids. However, handling such enormous amount of data is a challenge. LZMA and BZIP2 are two industrial strength compression techniques. In this paper we present an enhanced version of these two schemes specifically targeted to smart grid data through a pre-processing step. Our results show that while the original LZMA is able to compress the data size to around 80% our enhanced scheme using the preprocessing is able to reduce the size of the smart grid data to 98% on average.","PeriodicalId":408526,"journal":{"name":"2015 International Conference on Smart Cities and Green ICT Systems (SMARTGREENS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Enhanced LZMA and BZIP2 for improved energy data compression\",\"authors\":\"Zaid Bin Tariq, N. Arshad, M. Nabeel\",\"doi\":\"10.5220/0005454202560263\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Smart grid is the next generation of electricity production, transmission and distribution system. This is possible through an overlayed communication layer with the power delivery layer. Due to this communication layer smart grids produce enormous amounts of data. This data may be analyzed for improving the quality of service of smart grids. However, handling such enormous amount of data is a challenge. LZMA and BZIP2 are two industrial strength compression techniques. In this paper we present an enhanced version of these two schemes specifically targeted to smart grid data through a pre-processing step. Our results show that while the original LZMA is able to compress the data size to around 80% our enhanced scheme using the preprocessing is able to reduce the size of the smart grid data to 98% on average.\",\"PeriodicalId\":408526,\"journal\":{\"name\":\"2015 International Conference on Smart Cities and Green ICT Systems (SMARTGREENS)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Smart Cities and Green ICT Systems (SMARTGREENS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0005454202560263\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Smart Cities and Green ICT Systems (SMARTGREENS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0005454202560263","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhanced LZMA and BZIP2 for improved energy data compression
Smart grid is the next generation of electricity production, transmission and distribution system. This is possible through an overlayed communication layer with the power delivery layer. Due to this communication layer smart grids produce enormous amounts of data. This data may be analyzed for improving the quality of service of smart grids. However, handling such enormous amount of data is a challenge. LZMA and BZIP2 are two industrial strength compression techniques. In this paper we present an enhanced version of these two schemes specifically targeted to smart grid data through a pre-processing step. Our results show that while the original LZMA is able to compress the data size to around 80% our enhanced scheme using the preprocessing is able to reduce the size of the smart grid data to 98% on average.