I Q R based Approach for Energy Efficient Dynamic VM Consolidation for Green Cloud Data Centers

Abstract

With the advent of cloud computing in the arena of IT field energy consumption and service level agreement (SLA) violation emerge as a major problem, which reduces the profit of cloud service providers (CSP) and affect the cloud customers by fencing the reusability and scalability of the cloud data center services. This problem needs to be eradicate for the efficient resource provisioning in cloud data center. To satisfy the customer need virtual machine (VM) migration technique is required to balance the load of entire data center. Therefore we need to transfer the virtual machine of the overloaded host to the light weighted host using virtual machine migration technique. Due to frequent load balancing of cloud data center enormous amount of energy consumption takes place. This enhances the overall energy cost and degrades the performance of cloud data center. This paper proposes an Energy Efficient Dynamic VM Consolidation algorithm for reducing energy consumption.

Dynamic Optimization of Energy Efficiency and Service Level Agreement violation in Cloud Data Centers via Virtual Machine Consolidation

“…The objective extends beyond the mere reduction of energy consumption; it also encompasses the mitigation of the likelihood of other hosts transitioning into states of heaviness or lightness. This intricate method leverages the median technique [13] as an integral component within the broader framework of the Interquartile Range (IQR) algorithm [11]. The initial phase of the method entails the computation of the IQR threshold, a critical metric for the identification of host overloads or under-loads.…”

“…Furthermore, these methods predominantly center on a single performance metric, such as energy consumption or SLAv. For instance, the IQR algorithm [11] primarily relies on quartiles to establish threshold levels and identify physical hosts with high and low workloads, paying limited attention to the intricate process of selecting and migrating virtual machines. In contrast, contemporary approaches go beyond host categorization and prioritize the selection of virtual machines based on their energy consumption profiles, along with outlining the methodology for their reallocation to different physical hosts.…”

Detailed Analysis of Various Load Balancing and Power Reduction Methodology in Cloud Environment

“…The I Q R basedapproach [4], in this paper they adopt the idea of double threshold based algorithm, inter quartile range approach of load balancing and proposed an energy efficient approach in which, firstly the calculate upper and lower threshold to categories the hosts in data center. To calculate the threshold they arranger the utilization of the hosts in increasing order and divide the list by median than again calculate median of each list and uses these median as a upper and lower threshold.…”

“…In server consolidation we try to minimize the no of server running at a time while keeping in mind the SLA violation. To minimize the no of server running server at a time we shut down all idle server and saves the power consumption, in turn it saves the operational cost of the data center [4]. For that we uses the concept of VM migration.…”