Improving Cost for Data Migration in Cloud Computing Using Genetic Algorithm

Author:

Chawla Nitin1,Kumar Deepak1,Sharma Dinesh Kumar2

Affiliation:

1. Amity University, India

2. University of Maryland, Eastern Shore, USA

Abstract

Cloud computing is gradually increasing its popularity in enterprise-wide organizations. Information technology organizations e.g., IBM, Microsoft, and Amazon have already shifted towards Cloud computing. Cloud-based offerings such as Software as a Service, Platform as a Service and Infrastructure as a Service (IAAS) are the most famous offerings. Most of the existing enterprise applications are deployed using an on-premise model. Organizations are looking for Cloud based offerings to deploy or upgrade their existing applications. SAP, Microsoft Dynamics, and Oracle are the most famous ERP or CRM application OEMs. These enterprise applications generate lots of data are hosted in an organization or on client data centers. Moving data from one data center to the Cloud is always a challenging tasks which cost a lot and takes much effort. This study proposes an efficient approach to optimize cost for data migration in cloud computing. This study also proposes the approach to optimize cost for data collection from multiple locations which can be processed centrally and then migrate to Cloud Computing.

Publisher

IGI Global

Subject

Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Networks and Communications,Computer Science Applications,Software

Reference18 articles.

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4. Journey to Adoption of cloud;N.Chawla;of the National Conference on Computing, Communication and Information Processing (,2015

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