Adaptive Computational Solutions to Energy Efficiency in Cloud Computing Environment Using VM Consolidation

Abstract

Cloud Computing has emerged as a computing paradigm where services are provided through the internet in recent years. Offering on-demand services has transformed the IT companies' working environment, leading to a linearly increasing trend of its usage. The provisioning of the Computing infrastructure is achieved with the help of virtual machines. A great figure of physical devices is required to satisfy the users' resource requirements. To meet the requirements of the submitted workloads that are usually dynamic, the cloud data centers cause the over-provisioning of cloud resources. The result of this over-provisioning is the resource wastage with an increase in the levels of energy consumption, causing a raised operational cost. High CO 2 emissions result from this huge energy consumption by data centers, posing a threat to environmental stability. The environmental concern demands for the controlled energy consumption, which can be attained by optimal usage of resources to achieve in the server load, by minimizing the number of active nodes, and by minimizing the frequency of switching between active and de-active server mode in the data center. Motivated by these actualities, we discuss numerous statistical, deterministic, probabilistic, machine learning and optimization based computational solutions for the cloud computing environment. A comparative analysis of the computational methods, on the basis of architecture, consolidation step involved, objectives achieved, simulators involved and resources utilized, has also been presented. A taxonomy for virtual machine (VM) consolidation has also been derived in this research article followed by emerging challenges and research gaps in the field of VM consolidation in cloud computing environment.

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

“…The SLAv, as explained in section 2-3, consists of two components: SLATAH and PDM. Since contract violation is directly related to customer satisfaction rates [5,7,24], cloud providers strive to meet higher levels of customer demand, making every effort to reduce SLAv. The experimental datasets, evaluation metrics and evaluation of experimental results are presented in following.…”

“…• Number of migrations: Virtual machine migration is a time-consuming process, adding to system overhead, and increasing both energy consumption and network traffic. Therefore, an essential metric in determining the efficiency of the proposed method is the calculation of the number of migrations [24].…”

“…• Efficiency: Shutting down physical machines and placing them in a low-power state can increase their susceptibility to failures compared to machines that are always on [24,25]. Therefore, the efficiency of cloud computing systems decreases as the consolidation rate increases.…”

Host Detection and Classification using Support Vector Regression in Cloud Environment

“…Task scheduling is the process of task-resource mapping. By taking into account the attribute and status of cloud resources, the cloud system transfers these tasks to the related resources to run according to the attributes and necessities of these tasks (Magotra et al, 2022). Contrary to this, if scheduling is not done properly, several parameters are affected, namely, resource consumption is increased, task execution time is extended, the whole system's throughput is reduced, and resource life is also reduced.…”

An Efficient Task Scheduling for Cloud Computing Platforms Using Energy Management Algorithm: A Comparative Analysis of Workflow Execution Time

“…These techniques are known to give ideal results for job scheduling in a complex setting in a shorter amount of time. According to published research, HEFT [16] produces outstanding outcomes in respect of the timeliness and quality of the timetable. The first vacant space is chosen; however, in some circumstances, this may not result in a desirable solution.…”