期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2018
卷号：6
期号：2
页码：1316
DOI：10.15680/IJIRCCE.2017.0602126
出版社：S&S Publications
摘要：In current Technology world, the possibility of accounting overall resource usage in all applicationsbecome very difficult and providing security for the data stored in cloud becoming very tough .Nevertheless, in thedomains where small number of shared services serve to a plethora of different entities requests, auditing resourcewhich come to be significantly challenging. In the beginning, the global resource utilization at the shared service is theaccumulate of the resource utilization for number foreign entities whose identities are not exposed to the sharedservice. Second, even though such information available, normal monitoring tools (e.g., top) are not able to hand overcorrect break-down of resource utilization after all sharing occurs at sub instance level (i.e. service instances are notexclusive) and not able to provide security for the resources. We review inherent challenges of carrying out resourceutilization of shared resource and provide security to the resource stored in cloud by using encryption. To provide datasecure repository or data recovery in cloud storage we proposed muti-cloud architecture, where the user data is splitinto 2 parts and one half is encrypted using AES encryption algorithm and other half is encrypted using attribute basedencryption algorithm and stored in Cloud 1, Cloud 2. During the request our technique will merge the 2 parts andprovide the response to the requested user. We measure two non-interfering approaches having distinct balance amonglocal monitoring and collective inference – (1)Linear regression that makes uses of easily-available tools which givestotal measurement and executing well-known linear regression as inference, and (2) Rameter that inserts huge intensityon acquisition of fine-grained per-thread information from within the hypervisor and applying light inference on thedata
关键词：Cloud computing; Load balancing; Energy efficiency.
