Title: Efficient storage management framework for software defined cloud
Authors: Sonika Shrivastava; R.K. Pateriya
Addresses: Department of Computer Science and Engineering, Maulana Azad National Institute of Technology, Bhopal, M.P, 462003, India ' Department of Computer Science and Engineering, Maulana Azad National Institute of Technology, Bhopal, M.P, 462003, India
Abstract: The exponential growth of data is a matter of concern for every organisation. Storage of huge data mountain is only possible through adoption of cloud. Nowadays, popularity of software defined system is increasing and virtualised cloud data centre are also moving towards software defined data centre. This new change is possible only because of advancement in software defined network, software defined storage, etc. The main characteristics of software defined systems are abstraction layers or interfaces that hide the complexity and provide support for service management. Software defined storage allow user to properly communicate their storage needs and allow automated mobility and management of data which can reduce storage cost and enhances data reliability. This paper presents a framework to develop data management interface for software defined storage using well-known redundancy technique replication and erasure coding. This work focuses to solve the two issue reliability and cost of data storage in cloud by continuous monitoring and scanning of storage system. This new framework for software defined storage decreases the total cost of ownership and provide efficient technique for storage management in cloud which propel the development of software defined cloud.
Keywords: big data; cloud computing; cloud storage; erasure codes; reliability; replication; reedsolomon codes; software defined networking; SDN; software defined storage; SDStorage; software defined data centers; SDDC; software defined clouds; SDCloud.
International Journal of Internet Technology and Secured Transactions, 2017 Vol.7 No.4, pp.317 - 329
Received: 16 Dec 2016
Accepted: 08 Mar 2017
Published online: 04 May 2018 *