Y. Hashi, Kazuyoshi Matsumoto, Y. Seki, M. Hiji, Toru Abe, T. Suganuma
{"title":"Design and Implementation of Data Management Scheme to Enable Efficient Analysis of Sensing Data","authors":"Y. Hashi, Kazuyoshi Matsumoto, Y. Seki, M. Hiji, Toru Abe, T. Suganuma","doi":"10.1109/ICAC.2015.58","DOIUrl":null,"url":null,"abstract":"ICT supports smart communities in their aim to build efficient and sustainable social infrastructure. To realize a smart community, it is necessary to manage and analyze data about the community including large volumes of sensing data, meta-data, as well as information on data sources and consent for use, all of which are interrelated. We propose a data management scheme capable of both high-speed search of large volumes of data for analysis, and flexible search of data which changes depending on the collection environment. A major characteristic of our scheme is that it combines a schema-free, document-oriented database and an graph database suited for flexible search. We implement proposed data management scheme, and evaluate a performance of the search for sensing data. As the result, searching time of large volumes of sensing data is very high-speed. We believe that proposed data management scheme is able to minimize the the time required for analysis.","PeriodicalId":6643,"journal":{"name":"2015 IEEE International Conference on Autonomic Computing","volume":"93 1","pages":"319-324"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Autonomic Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAC.2015.58","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
ICT supports smart communities in their aim to build efficient and sustainable social infrastructure. To realize a smart community, it is necessary to manage and analyze data about the community including large volumes of sensing data, meta-data, as well as information on data sources and consent for use, all of which are interrelated. We propose a data management scheme capable of both high-speed search of large volumes of data for analysis, and flexible search of data which changes depending on the collection environment. A major characteristic of our scheme is that it combines a schema-free, document-oriented database and an graph database suited for flexible search. We implement proposed data management scheme, and evaluate a performance of the search for sensing data. As the result, searching time of large volumes of sensing data is very high-speed. We believe that proposed data management scheme is able to minimize the the time required for analysis.