{"title":"高效管理科学应用的分布式云计算系统","authors":"Anil Bamwal","doi":"10.1109/CONFLUENCE.2017.7943160","DOIUrl":null,"url":null,"abstract":"This paper defines how a distributed cloud computing system is used to define different efficient scientific applications. Generally a distributed cloud computing system is formed from a number of different Infrastructure-as-a-Service (IaaS) clouds which are used in an integrated infrastructure. The production of distributed cloud is continuing since last four years with around 800,000 numbers of completed jobs with an average of about 500 simultaneous and parallel jobs which are executed for about 12 hours per day. Here the design and implementation of system is reviewed based on some custom components and a number of pre-existing components. In this paper the various operations of the system, plans for increasing the computing capacity and expansion to more number of sites is discussed.","PeriodicalId":6651,"journal":{"name":"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence","volume":"1 1","pages":"262-268"},"PeriodicalIF":0.0000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Efficient management of distributive cloud computing system for scientific applications\",\"authors\":\"Anil Bamwal\",\"doi\":\"10.1109/CONFLUENCE.2017.7943160\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper defines how a distributed cloud computing system is used to define different efficient scientific applications. Generally a distributed cloud computing system is formed from a number of different Infrastructure-as-a-Service (IaaS) clouds which are used in an integrated infrastructure. The production of distributed cloud is continuing since last four years with around 800,000 numbers of completed jobs with an average of about 500 simultaneous and parallel jobs which are executed for about 12 hours per day. Here the design and implementation of system is reviewed based on some custom components and a number of pre-existing components. In this paper the various operations of the system, plans for increasing the computing capacity and expansion to more number of sites is discussed.\",\"PeriodicalId\":6651,\"journal\":{\"name\":\"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence\",\"volume\":\"1 1\",\"pages\":\"262-268\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CONFLUENCE.2017.7943160\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CONFLUENCE.2017.7943160","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient management of distributive cloud computing system for scientific applications
This paper defines how a distributed cloud computing system is used to define different efficient scientific applications. Generally a distributed cloud computing system is formed from a number of different Infrastructure-as-a-Service (IaaS) clouds which are used in an integrated infrastructure. The production of distributed cloud is continuing since last four years with around 800,000 numbers of completed jobs with an average of about 500 simultaneous and parallel jobs which are executed for about 12 hours per day. Here the design and implementation of system is reviewed based on some custom components and a number of pre-existing components. In this paper the various operations of the system, plans for increasing the computing capacity and expansion to more number of sites is discussed.