Implementation and Validation of the Optimized Deduplication Strategy in Federated Cloud Environment
Source abstract
Abstract
Cloud computing technology is the culmination of technical advancements in computer networks, hardware and software capabilities that collectively gave rise to computing as a utility. It offers a plethora of utilities to its clients worldwide in a very cost-effective way and this feature is enticing users/companies to migrate their infrastructure to cloud platform. Swayed by its gigantic capacity and easy access clients are uploading replicated data on cloud resulting in an unnecessary crunch of storage in datacenters. Many data compression techniques came to rescue but none could serve the purpose for the capacity as large as a cloud, hence, researches were made to de-duplicate the data and harvest the space from exiting storage capacity which was going in vain due to duplicacy of data. For providing better cloud services through scalable provisioning of resources, interoperability has brought many Cloud Service Providers (CSPs) under one umbrella and termed it as Cloud Federation. Many policies have been devised for private and public cloud deployment models for searching/eradicating replicated copies using hashing techniques. Whereas the exploration for duplicate copies is not restricted to any one type of CSP but to a set of public or private CSPs contributing to the federation. It was found that even in advanced deduplication techniques for federated clouds, due to the different nature of CSPs, a single file is stored at private as well as public group in the same cloud federation which can be handled if an optimized deduplication strategy be rendered for addressing this issue. Therefore, this study has been aimed to further optimize a deduplication strategy for federated cloud environment and suggested a central management agent for the federation. It was perceived that work relevant to this is not existing, hence, in this paper, the concept of federation agent has been implemented and deduplication technique following file level has been used for the accomplishment of this approach.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Cloud Data Security Solutions · Blockchain Technology Applications and Security · Caching and Content Delivery
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (29)
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