S
Sandeep Gopisetty
Researcher at IBM
Publications - 64
Citations - 1138
Sandeep Gopisetty is an academic researcher from IBM. The author has contributed to research in topics: Cloud computing & Storage area network. The author has an hindex of 20, co-authored 62 publications receiving 1112 citations.
Papers
More filters
Patent
Server consolidation using virtual machine resource tradeoffs
TL;DR: In this article, a virtual machine is assigned to a target physical server based on a plurality of virtualization parameters for maximizing utility of virtual machines and physical servers in server consolidation using virtual machine resource tradeoffs.
Patent
Remote data protection in a networked storage computing environment
TL;DR: In this article, a data protection approach is disclosed for protecting data at both the file system level and application level, which can be used to restore the state of a computer file system to that of a given point in time.
Patent
Apparatus, system, and method for interaction with multi-attribute system resources as groups
Andreas Dieberger,Sandeep Gopisetty,Eser Kandogan,Cheryl A. Kieliszewski,Roberto C. Pineiro,Chung-Hao Tan +5 more
TL;DR: In this paper, an apparatus, system, and method for interacting with multi-attribute managed resources as groups is described. But the method is not described in detail and it is assumed that each set of managed resources in a set comprises the same value for the target attribute.
Patent
End-to end provisioning of storage clouds
TL;DR: In this article, an integrated provisioning framework that automates the process of provisioning storage resources, end-to-end, for an enterprise storage cloud environment is presented. But, it does not address the problem of workload requirements and configuration for available system resources.
Patent
Data lifecycle management within a cloud computing environment
TL;DR: In this paper, a set of policies can be defined that allow for automatic valuation of the data and migration of data between different storage tiers before a policy set is deployed, it can be assessed to determine effects it will have on cost, performance, and data location based on data characteristics and access patterns.