Economic and Energy Optimization by Joint Scheduling in Cloud Computing
Journal Title: Elysium Journal of Engineering Research and Management - Year 2016, Vol 4, Issue 3
Abstract
Cloud computing technologies have empowered a new-fangled paradigm for progressive product advancement by the establishment and contribution of services in a multi-tenant disseminated simulation environment. A novel joint scheduling and computation offloading (JSCO) is invented where an optimal decision is made on mechanisms to be offloaded as well as the forecasting the mandate mechanisms. A systematic framework for monitoring, analysing and improving system performance is proposed in this research.The basic prototype of the two resource augmentation environments is to provide computation resources to user systems. Thus, the method of offloading a task onto the local private cloud involves only the energy consumption at the time of transferring data. On the other hand, offloading onto the public clouds involves: (i) energy consumption incurred when transferring data, and (ii) monetary cost incurred when using computing resources per unit time, and transferring data per unit bytes.This approach adds the service tenants to matched virtual machines and allocates the virtual machines to physical host machines using a best-fit heuristic approach. The Performance analysis determine the effectiveness of best-fit heuristic approach by allocating virtual machines to hosts by utilizing their capacity.
Authors and Affiliations
Kavitha A.
Keywords
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