An intelligent approach for virtual machine and QoS provisioning in cloud computing

Abstract

Cloud Computing has become the most popular distributed computing environment because it does not require any user level management and controlling on the low-level implementation of the system. However, efficient resource provisioning is a key challenge for cloud computing and resolving such kind of problem can reduce under or over utilization of resources, increase user satisfaction by serving more users during peak hours, reduce implementation cost for providers and service cost for users. Existing works on cloud computing focuses to accurate estimation of the capacity needs, static or dynamic VM (Virtual Machine) creation and scheduling. But significant amount of time is required to create and destroy VMs which could be used to serve more user requests. In this paper, an adaptive QoS (Quality of Service) aware VM provisioning mechanism is developed that ensures efficient utilization of the system resources. The VM for similar type of requests has been recycled so that the VM creation time can be minimized and used to serve more user requests. In the proposed model, QoS is ensured by serving all the tasks within the requirements described in SLA. Tasks are separated using multilevel queue and the most urgent task is given high priority. The simulation-based experimental results shows that a great number of tasks can be served compared to others which will help to satisfy customers during the peak hour.

Multi-Objective Tasks Scheduling Algorithm for Cloud Computing Throughput Optimization

“…At runtime broker decides mapping of task to a VM. Sometimes single tasks with multiple users [3] are mapped to VM and sometimes from a group of task a particular task is picked up for the allocation of VM depending upon the execution time and arrival time [6,7,9,12,16]. The tasks in the group is selected sequentially and submitted to the Virtual Machine.…”

Optimization of Task Scheduling Algorithm through QoS Parameters for Cloud Computing

“…Similar work is done in [17,18,19] where scheduling is done in order to reduce execution time and arrival time. Authors in [20] proposed a Dynamic task scheduling scheme DGS which allocates computing tasks to the virtual machines using greedy strategy and the scheme results in reduction in the completion time and improvement in the resource utilization.…”

Recent Trends towards Green Clouds by using Fuzzy based Live Migration

“…IaaS administrators can use their brings about rapidly assess probable savings in device uptime and, ergo, untapped energy saving potential. A.K.Das et al [10] created an flexible QoS (Quality of Service) conscious VM provisioning system that ensured efficient usage of the device resources. The VM for related form of requests have been recycled so your VM creation time could be minimized and used to serve more consumer requests.…”