T.Thiruvenkadam et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.6, June- 2014, pg. 837-842 © 2014, IJCSMC All Rights Reserved 837 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology ISSN 2320–088X IJCSMC, Vol. 3, Issue. 6, June 2014, pg.837 – 842 RESEARCH ARTICLE An Approach to Virtual Machine Placement Problem in a Datacenter Environment Based On Overloaded Resource Mr. T.Thiruvenkadam Dr. V.Karthikeyani Asst.Professor, Department of Computer Science, Asst.Professor, Department of Computer Science, K.S.Rangasamy College of Arts and Science, Thiruvalluvar Govt., Arts College, Tiruchengode, India Rasipuram, India Abstract — The arrival of the clouds has introduced very strict initiative over the physical resources. A typical resource management system receives queues and finally matches user job requirements with the characteristics of the offered hardware. Server overload is the basis of resource insufficiency and spoils the performance of applications which leads to affect the QoS. Lively consolidation of Virtual Machines is an efficient way to get better use of resources and power efficiency in Cloud data centers. Identifying when it is best to move VMs from a congested host is an aspect of Lively VM consolidation that directly influences the resource consumption and Quality of Service (QoS) delivered by the system. This paper focus on the importance of the detection of server overload and compares the various scheduling algorithms currently used for scheduling virtual machines and also proposes the design methodology of a new algorithm that helps to improve the resource utilization and at the same time energy efficiency. Keywords: Virtual Machines, Overloaded resources, Server Consolidation, Hypervisor, Load Balancing I. INTRODUCTION One of the major causes of energy inefficiency in data centers is the idle power [1] Data center costs can be reduced by utilizing virtual machines (VMs). Using virtualization, multiple operating system instances can run on the same physical machine, exploiting hardware capabilities more fully, allowing administrators to save money on hardware and energy costs. To maximize the savings, administrators should assign as many VMs as possible to servers given performance requirements. We refer to this problem as the Virtual Machine Assignment Problem. The scheduling of virtual machines in a cloud computing environment has become crucial due to the increase in the number of users. This is usually done to load balance a system effectively or to achieve a target quality of service [2]. The scheduling algorithm used contributes to the performance of the entire system and the throughput. Server consolidation is the practice of migrating distinct legacy servers from distinct physical machines that possibly use different operating systems to virtual machines on a single more powerful platform. This reduces operational expenses by saving the need to maintain and support all those legacy systems, reducing the floor footprint, and reducing power and cooling requirements. It is especially beneficial when it increases server utilization, e.g. if the legacy servers are not highly utilized, but when consolidated