Cross-Correlation Prediction of Resource Demand for Virtual Machine Resource Allocation in Clouds

2014 ◽  
Author(s):  
Dorian Minarolli ◽  
Bernd Freisleben
Keyword(s):  
Resource Allocation ◽  
Virtual Machine ◽  
Cross Correlation ◽  
Resource Demand

Distance Aware VM allocation process to minimize energy consumption in cloud computing

2019 ◽  
Vol 12 ◽  
Author(s):  
Gurpreet Singh ◽  
Manish Mahajan ◽  
Rajni Mohana
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Research Work ◽  
Service Level Agreement ◽  
Service Level ◽  
Physical Machine ◽  
Allocation Process

BACKGROUND: Cloud computing is considered as an on-demand service resource with the applications towards data center on pay per user basis. For allocating the resources appropriately for the satisfaction of user needs, an effective and reliable resource allocation method is required. Because of the enhanced user demand, the allocation of resources has now considered as a complex and challenging task when a physical machine is overloaded, Virtual Machines share its load by utilizing the physical machine resources. Previous studies lack in energy consumption and time management while keeping the Virtual Machine at the different server in turned on state. AIM AND OBJECTIVE: The main aim of this research work is to propose an effective resource allocation scheme for allocating the Virtual Machine from an ad hoc sub server with Virtual Machines. EXECUTION MODEL: The execution of the research has been carried out into two sections, initially, the location of Virtual Machines and Physical Machine with the server has been taken place and subsequently, the cross-validation of allocation is addressed. For the sorting of Virtual Machines, Modified Best Fit Decreasing algorithm is used and Multi-Machine Job Scheduling is used while the placement process of jobs to an appropriate host. Artificial Neural Network as a classifier, has allocated jobs to the hosts. Measures, viz. Service Level Agreement violation and energy consumption are considered and fruitful results have been obtained with a 37.7 of reduction in energy consumption and 15% improvement in Service Level Agreement violation.

Virtual Machine Placement Using Statistical Mechanism in Cloud Computing Environment

2018 ◽  
Vol 9 (3) ◽  
pp. 23-31
Author(s):  
Narander Kumar ◽  
Surendra Kumar
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Virtual Machine ◽  
Minimum Cost ◽  
Virtual Machine Placement ◽  
The Internet ◽  
Computing Environment ◽  
Assignment Problems ◽  
Cloud Computing Environment ◽  
Statistical Mechanism

The internet has become essential and is the basis of cloud computing and will continue to be in the future. Best resource allocation is a process of placing the resources at their minimum cost/time and minimizes the load to a virtual machine. In this article, the authors propose an algorithm to optimize assignment problems and get the best placements in the resources to maintain the load on the virtual machine. Further, they also make comparisons between various optimization mechanisms for assignment problems, which is formulated for the cloud in virtual machine placement.

scholarly journals A Novel Energy Efficient Resource Management System in Cloud Computing Environment.

2018 ◽  
Vol 7 (4.19) ◽  
pp. 1030
Author(s):  
S. K. Sonkar ◽  
M. U.Kharat
Keyword(s):  
Resource Allocation ◽  
Energy Consumption ◽  
Resource Management ◽  
Virtual Machine ◽  
Energy Efficient ◽  
Service Providers ◽  
Optimization Techniques ◽  
Cloud Provider ◽  
Efficient Resource ◽  
Machine Allocation

Primary target of cloud provider is to provide the maximum resource utilization and increase the revenue by reducing energy consumption and operative cost. In the service providers point of view, resource allocation, resource sharing, migration of resources on demand, memory management, storage management, load balancing, energy efficient resource usage, computational complexity handling in virtualization are some of the major tasks that has to be dealt with. The major issue focused in this paper is to reduce the energy consumption problem and management of computation capacity utilization.  For the same, an energy efficient resource management method is proposed to grip the resource scheduling and to minimize the energy utilized by the cloud datacenters for the computational work. Here a novel resource allocation mechanism is proposed, based on the optimization techniques. Also a novel dynamic virtual machine (VM) allocation method is suggested to help dynamic virtual machine allocation and job rescheduling to improve the consolidation of resources to execute the jobs. Experimental results indicated that proposed strategy outperforms as compared to the existing systems.  

Stability control in virtual machine: Resource allocation for cloud computing

2019 ◽  
Author(s):  
Mohd Badrulhisham Ismail ◽  
Habibah Hashim ◽  
Yusnani Mohd Yusof
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Virtual Machine ◽  
Stability Control

scholarly journals QoS Guaranteed Resource Allocation for Live Virtual Machine Migration in Edge Clouds

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 78441-78451
Author(s):  
Lei Yang ◽  
Doudou Yang ◽  
Jiannong Cao ◽  
Yuvraj Sahni ◽  
Xiaohua Xu
Keyword(s):  
Resource Allocation ◽  
Virtual Machine ◽  
Virtual Machine Migration
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