International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 6 Issue: 3 06 - 13 ______________________________________________________________________________________ 6 IJRITCC | March 2018, Available @ http://www.ijritcc.org _______________________________________________________________________________________ An optimal VM Placement, Energy Efficient and SLA at Cloud Environment - A Comparative Analysis Md.Rafeeq 1 , Dr.C.Sunil Kumar 2 , Dr.N.Subhash Chandra 3 1 Associate Professor, Dept of CSE, CMRTC, Hyderabad, Telangana, India: rafeeq.mail@gmail.com 2 Professor in IT, SNIST, Yamnampet, Ghatkesar,Hyderabad, Telangana, India: ccharupalli@gmail.com 3 Professor in CSE,CVRCE,Manglapalli, Ibrahimpatnam R.R(D), Telangana, India:subhashchandra.n.cse@gmail.com Abstract- In the cloud computing framework, computing resources can be increased or decreased in response to the users’ different application loads. The data is stored and the applications are running on the servers in the clouds. Users do not have to worry about lost or corrupt data. The clouds can distribute computing resources according to the users’ needs or preferences to provide fl exible management. Users do not have to buy expensive computing devices. They only need to pay for the computing services provided by the clouds. Cloud computing provides a platform for computational experiments with abundant computing and storage resources. The system can be considered as a whole and the control and management decisions are sent as services to agents. The challenge in the present study is to reduce energy consumption thus guarantee Service Level Agreement (SLA) at its highest level. Keywords — load balancing, Service level agreement, Code Shortening, Energy efficient, Quality of Service (QoS), Service Level Agreements (SLA), Virtual Machine (VM), VM Allocation Performance Comparison, Evolution Application, Response Time Comparison. __________________________________________________*****_________________________________________________ 1. INTRODUCTION The load balancing techniques brings the advantage of lower response time [1]. However the cost of replication of resources is also to be taken care as an additional cost. The cloud data center based load balancing is distinguished from the domain name service based load balancing. The domain name service load balancers deploys the hardware and software components to balance load for the hardware resources, whereas the cloud based load balancing techniques deploys the software algorithms or protocols to distribute the load over multiple data center nodes. However the recent researches constraint to achieve the optimal SLA violation during VM Migration. Thus this work demonstrates A Service Level Agreement Effective Optimal Virtual Machine Migration Technique for Load Balancing on Cloud Data Centers using proposed three phase optimal virtual machine migration technique. To address this problem, the adoption of a technology called Virtualization is embraced. Through virtualization, a physical server can create multiple instances of virtual machines on it, where each virtual machine defines virtual hardware and software package on behalf of a physical server. In IaaS model, infrastructure requests are mainly served by allocating the VMs to cloud users [2]. Successful live migration of VMs among host to host without significant interruption of service results in dynamic consolidation of VMs. However, high variable workloads can cause performance degradation when an application requires increasing demand of resources. Besides power consumption we need to consider the performance as it puts Quality of Service (QoS) which is defined via Service Level Agreement (SLA). Storage systems come in all shapes and sizes, but one thing that they all have in common is that components fail, and when a component fails, the storage system is doing the one thing it is not supposed to do: losing data. Failures are varied, from disk sectors becoming silently corrupted, to entire disks or storage sites becoming unusable. The storage components themselves are protected from certain types of failures. To deal with these failures, storage systems rely on erasure codes. An erasure code adds redundancy to the system to tolerate failures. The simplest of these is replication, such as RAID-1, where each byte of data is stored on two disks. In that way any failure scenario may be tolerated, so long as every piece of data has one surviving copy. Replication is conceptually simple. 2. LITERATURE REVIEW The Dynamic consolidation of virtual machines (VMs) is an effective way to improve the utilization of resources and energy efficiency in cloud data centers. Determining when it is best to reallocate VMs from an overloaded host is an aspect of dynamic VM consolidation that directly influences the resource utilization and quality of service (QoS) delivered by the system.comparing opti algorithm with few standard algorithms. INTER-QUARTILE RANGE It is method to allocation of virtual machine in cloud system. It is method of adaptive utilization Threshold which is work statics. (IQR) interquartile range IQR= Q3- Q1, it is very similar of MAD(mean absolute deviation ). MAD is another algorithm adaptive utilization Threshold. We define the upper utilization threshold shown in (i) Tu = 1- S.IQR………………..(i ) Maximum correlation The Maximum Correlation (MC) policy is based other idea proposed by Verma et al. [7]. The idea is that the higher the correlation between theresource usage by applications running on an oversubscribed server[3].In [6] explain memory, CPU utilization and power