期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2013
卷号：4
期号：6-4
出版社：Seventh Sense Research Group
摘要：Enterprise storage is the computer data storage designed for largescale, hightechnology environments of the modern enterprises which is very time efficient where in stored data can be accessed in less time. When comparing to the consumer storage, it has higher scalability, higher reliability and better fault tolerance. As well, criticality of data varies between enterprises. Challenges faced in current scenario to store big data are in terms of cost, data loss, efficiency while accessing data, maintaining consistency of data and many more. In order to provide better storage solution and data management, the proposed solution came up with platform of Workflow Automation (WFA). WFA is an active management tool which directly allocates storage on storage server based on client request. It depends on a data source i.e., OnCommand Unified Manager (OCUM) to monitor the storage components. OCUM acts as a passive reporting tool, which polls all the storage data at different time stamps. The monitored data includes parameters and attributes of storage component like corrupted disk data, normal disk data or may be some lack of storage space. WFA has cache based intelligence and it acquires only relevant data of context from OCUM. Based on this acquired cache data, WFA can provide better storage solutions and data management by which it takes care of conditions like maintaining health of storage and takes appropriate actions like migrating data, replacing corrupted disk etc., The acquired cache data can be queried by filter/ finders to select storage component as a resource on which data is stored. The results of which will work on selective resource, to execute specific task of interest using workflows. Query results return the count of storage components and related information to verify consistency and no data loss from any storage resource. Hence the proposed solution helps in performance tuning of big data storage solutions in terms of data access time, reliability, efficiency, data consistency and security. It reduces the cost of managing storage, enables adherence to best practices for storage processes.
