Energy-Saving Virtual Machine Placement Method for User Experience in Cloud Environment

Abstract

Green computing focuses on the energy consumption to minimize costs and adverse environmental impacts in data centers. Improving the utilization of host computers is one of the main green cloud computing strategies to reduce energy consumption, but the high utilization of the host CPU can affect user experience, reduce the quality of service, and even lead to service-level agreement (SLA) violations. In addition, the ant colony algorithm performs well in finding suitable computing resources in unknown networks. In this paper, an energy-saving virtual machine placement method (UE-ACO) is proposed based on the improved ant colony algorithm to reduce the energy consumption and satisfy users’ experience, which achieves the balance between energy consumption and user experience in data centers. We improve the pheromone and heuristic factors of the traditional ant colony algorithm, which can guarantee that the improved algorithm can jump out of the local optimum and enter the global optimal, avoiding the premature maturity of the algorithm. Experimental results show that compared to the traditional ant colony algorithm, min-min algorithm, and round-robin algorithm, the proposed algorithm UE-ACO can save up to 20%, 24%, and 30% of energy consumption while satisfying user experience.

A Harris Hawk Optimisation system for energy and resource efficient virtual machine placement in cloud data centers

“…To minimise energy consumption and fulfil uers' experience, an enhanced ant colony algorithm is used to propose an energy-saving VMP approach which attains a balance between user experience and energy consumption in data centres [9]. The original ant colony algorithm's pheromone and heuristic parameters were modified, ensuring that the improved algorithm may transition from a local to a globally optimal solution, avoiding the algorithm's early maturity.…”

Multi-Objective Virtual Machine Placement using Order Exchange and Migration Ant Colony System Algorithm

“…They used mathematical modeling to place virtual machine cloud. Work described in [18] minimizes the network traffic for placing the virtual machines and compared their model with VMP algorithm, it is observed that their model reduced power energy consumption by 3.5%.…”

Dynamic virtual machine relocation system for energy‐efficient resource management in the cloud

“…Cloud computing provides a compelling model for changing the work environment of IT companies, so cloud computing trends are on the rise. Among the various services in the cloud environment, IaaS includes Amazon, Google, and Microsoft, the leading commercial service providers that have developed a usage payment model based on this model to providers offer these services to users 1 . It takes a lot of PMs to meet the needs of cloud users and much energy to power and cool the various electronic modules within these systems 2 .…”

“…The inactive servers go into the low-energy mode or are turned off to reduce the static energy consumption of servers, thus reducing the total energy consumption of the data center. However, before moving a VM, there are some important issues to consider: (1) the migration time of the virtual machine, that is, the trigger time; (2) the assortment of the VM to be migrated; and (3) which host should be selected to support the VM selected for relocation, that is, the host location.…”