Hybrid Scheduler for Minimum Energy Consumption and Optimised Job Management in Data Centre
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 8
Abstract
Today cloud data centers play an very important role in Information Technology sector (ITC). Power consumption and utilization is the major problem in data centers. High use of energy rise the temperature in data centers which arises many big problems like hardware failure, network failure, unfriendly working environment and rise in various technical problems. So, cooling of data centers is an important need for easy working condition. So, Green Computing can be used to handle this problem. Green Cloud Computing (GCC) reduces the operational cost and save the energy. Dynamic consolidation of Green Cloud Computing presents a significant opportunity to save energy in data centers. A Green Cloud Computing (GCC) consolidation approach uses live migration of VMs so that some of the under-loaded Physical Machines (PMs) can be switchedoff or put into a low-power mode. On the other hand, achieving the desired level of Quality of Service (QoS) between cloud providers and their users is critical. Therefore, the main challenge is to reduce energy consumption of data centers while satisfying QoS requirements. With Green Cloud Computing it is possible to maintain the task scheduling in a perfect manner which cause a high quality difference in the present conditions of data centers. The current research concern is the unwanted power utilization, energy consumption and more time consumption in data center which is exceptionally gaining attention of researchers with respect to scheduling of the computing resources.. In this research proposal hybridization of multilevel feedback queue scheduling and weighted round robin is used to achieve above problem. With this approach we can maintain the minimum consumption of energy and providing a better response time.
Authors and Affiliations
Suman Kumar Mishra, Sachin Majithia
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