Abstract
The present study aims at recognizing the problem of dynamic virtual machine (VM) Consolidation using virtualization, live migration of VMs from underloaded and overloaded hosts and switching idle nodes to the sleep mode as a very effective approach for utilizing resources and accessing energy efficient cloud computing data centres. The challenge in the present study is to reduce energy consumption thus guarantee Service Level Agreement (SLA) at its highest level. The proposed algorithm predicts CPU utilization in near future using Time-Series method as well as Simple Exponential Smoothing (SES) technique, and takes appropriate action based on the current and predicted CPU utilization and comparison of their values with the dynamic upper and lower thresholds. The four phases in this algorithm include identification of overloaded hosts, identification of underloaded hosts, selection of VMs for migration and identification of appropriate hosts as the migration destination. The study proposes solutions along with dynamic upper and lower thresholds in regard with the first two phases. By comparing current and predicted CPU utilizations with these thresholds, overloaded and underloaded hosts are accurately identified to let migration happen only from the hosts which are currently as well as in near future overloaded and underloaded. The authors have used Maximum Correlation (MC) VM selection policy in the third phase, and attempted in phase four such that hosts with moderate loads, i.e. not overloaded hosts, liable to overloading and underloaded, are selected as the migration destination. The simulation results from the Clouds framework demonstrate an average reduction of 83.25, 25.23 percent and 61.1 in the number of VM migrations, energy consumption and SLA violations (SLAV), respectively.
Highlights
According to the definition provided by NIST [1] "cloud computing is a model for enabling ubiquitous, convenient, ondemand network access to a shared pool of configurable computing resources
Six parameters were used to assess and compare the proposed algorithm with those of other studies. These metrics included the number of virtual machine (VM) migrations from overloaded and underloaded hosts, the total energy consumption of physical resources, performance degradation due to VM Migration (PDM) [8], Service Level Agreement (SLA) Violation Time per Active Host (SLATAH) [8], which can be defined as the percentage of the period when the host experiences a CPU utilization of 100%, the researchers calculated the combined metric SLA violations (SLAV) by multiplying PDM with SLATAH [8] and indicated the duration in which the allocated resources to the host is lower than the required amount, ESV combined metric which is calculated by multiplication of total energy consumption with SLA violation [8] and is used to measure the simultaneous improvements in both metrics and indicates the trade-off between them
SLA violation was decreased by eliminating unnecessary migrations, since migrations only took place on overloaded hosts
Summary
According to the definition provided by NIST [1] "cloud computing is a model for enabling ubiquitous, convenient, ondemand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications and services). According to the reports published by Microsoft [5], the consumed energy used by physical resources can account for 45 percent of the operational costs in a data centre This amount has multiplied in the last five years [6]. The present study recognizes the problem of dynamic virtual machine Consolidation using virtualization, live migration of VMs from underloaded and overloaded hosts and switching idle nodes to the sleep mode, as a very effective approach for utilizing resources and accessing energy efficient cloud computing data centres [8,9,10,11]. The challenges faced are the consolidation of VMs and their allocation and placement on physical service providers in a way that they minimized energy consumption in the entire data centre and the number of active hosts as well as SLA violation, which is a contract between the clients and the providers.
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