{"title":"Scalability and performance analysis of CRUD matrix based fragmentation technique for distributed database","authors":"S. I. Khan, A. S. M. L. Hoque","doi":"10.1109/ICCITECHN.2012.6509702","DOIUrl":null,"url":null,"abstract":"Distributed processing is an efficient way to improve performance of a database management system significantly. Distribution of data involves fragmentation, replication and allocation process. Previous research works provided fragmentation solution based on empirical data which are not applicable at the initial stage of a distributed database. In this paper we have presented a fragmentation technique that can be applied at the initial stage when no experimental data are present as well as in later stages of a distributed database system for partitioning the relations. Scalability of our proposed technique also investigated for different situation those may arise in practical cases of a distributed database. Experimental results show that our technique can solve initial fragmentation problem of distributed database system properly also compete with other non initial fragmentation techniques quite good in later stages.","PeriodicalId":127060,"journal":{"name":"2012 15th International Conference on Computer and Information Technology (ICCIT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 15th International Conference on Computer and Information Technology (ICCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCITECHN.2012.6509702","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
Distributed processing is an efficient way to improve performance of a database management system significantly. Distribution of data involves fragmentation, replication and allocation process. Previous research works provided fragmentation solution based on empirical data which are not applicable at the initial stage of a distributed database. In this paper we have presented a fragmentation technique that can be applied at the initial stage when no experimental data are present as well as in later stages of a distributed database system for partitioning the relations. Scalability of our proposed technique also investigated for different situation those may arise in practical cases of a distributed database. Experimental results show that our technique can solve initial fragmentation problem of distributed database system properly also compete with other non initial fragmentation techniques quite good in later stages.