An efficient resource utilization technique for consolidation of virtual machines in cloud computing environments

2016 ◽  
Author(s):  
Gamal Eldin I. Selim ◽  
Mohamed A. El-Rashidy ◽  
Nawal A. El-Fishawy
Keyword(s):  
Cloud Computing ◽  
Resource Utilization ◽  
Virtual Machines ◽  
Efficient Resource ◽  
Computing Environments

scholarly journals A Game Theory Approach to Fair and Efficient Resource Allocation in Cloud Computing

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Xin Xu ◽  
Huiqun Yu
Keyword(s):  
Cloud Computing ◽  
Resource Utilization ◽  
Resource Sharing ◽  
Virtual Machines ◽  
Utilization Rate ◽  
Resources Allocation ◽  
Theory Approach ◽  
On Demand ◽  
Efficient Resource ◽  
Game Theoretic

On-demand resource management is a key characteristic of cloud computing. Cloud providers should support the computational resource sharing in a fair way to ensure that no user gets much better resources than others. Another goal is to improve the resource utilization by minimizing the resource fragmentation when mapping virtual machines to physical servers. The focus of this paper is the proposal of a game theoretic resources allocation algorithm that considers the fairness among users and the resources utilization for both. The experiments with an FUGA implementation on an 8-node server cluster show the optimality of this algorithm in keeping fairness by comparing with the evaluation of the Hadoop scheduler. The simulations based on Google workload trace demonstrate that the algorithm is able to reduce resource wastage and achieve a better resource utilization rate than other allocation mechanisms.

Dynamic Computation of Threshold Value for Classifying Jobs in Cloud Computing for Efficient Resource Utilization

2020 ◽  
Vol 17 (9) ◽  
pp. 4458-4461
Author(s):  
B. K. Dhanalakshmi ◽  
K. C. Srikantaiah ◽  
K. R. Venugopal
Keyword(s):  
Cloud Computing ◽  
Resource Utilization ◽  
Virtual Machines ◽  
Threshold Value ◽  
Experimental Result ◽  
Allocation Of Resources ◽  
Use Of Resources ◽  
Initial Stage ◽  
Dynamic Computation ◽  
Efficient Resource

Cloud computing is an instant use of resources and it is a trending technology in the field of computer science. Here, many jobs will be arriving continuously with different job size, at that point of time, allocating of resources for suitable virtual machines without allowing virtual machine to starving is a hindrance job. So, to avoid this hindrance, an algorithm Dynamic Computation of Threshold Value is proposed (DCTV) and based on the threshold value the jobs are classified in the initial stage, so this classification leads to allocation of resources precisely and efficient resource utilization. The experimental result shows that by using dynamic computation of threshold value the allocation of resource time is reduced and classification accuracy is improved compared to manual computation of threshold value.

scholarly journals ALGORITHM FOR TASK CONSOLIDATION IN CLOUD COMPUTING: A COMPARATIVE SURVEY

2018 ◽  
Vol 6 (5) ◽  
pp. 340-345
Author(s):  
Rajat Pugaliya ◽  
Madhu B R
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Resource Utilization ◽  
Service Provider ◽  
Virtual Machines ◽  
Cloud Service ◽  
Cloud Service Provider ◽  
Dynamic Task ◽  
Main Challenge ◽  
High Level

Cloud Computing is an emerging field in the IT industry. Cloud computing provides computing services over the Internet. Cloud Computing demand increasing drastically, which has enforced cloud service provider to ensure proper resource utilization with less cost and less energy consumption. In recent time various consolidation problems found in cloud computing like the task, VM, and server consolidation. These consolidation problems become challenging for resource utilization in cloud computing. We found in the literature review that there is a high level of coupling in resource utilization, cost, and energy consumption. The main challenge for cloud service provider is to maximize the resource utilization, reduce the cost and minimize the energy consumption. The dynamic task consolidation of virtual machines can be a way to solve the problem. This paper presents the comparative study of various task consolidation algorithms.

scholarly journals ENERGY EFFICIENT LOAD BALANCING FOR CLOUD DATA CENTER

2017 ◽  
Vol 10 (13) ◽  
pp. 162
Author(s):  
Amey Rivankar ◽  
Anusooya G
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Energy Efficient ◽  
Large Scale ◽  
Virtual Machines ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Efficient Resource ◽  
Cloud Data Centers ◽  
Near Future

Cloud computing is the latest trend in large-scale distributed computing. It provides diverse services on demand to distributive resources such asservers, software, and databases. One of the challenging problems in cloud data centers is to manage the load of different reconfigurable virtual machines over one another. Thus, in the near future of cloud computing field, providing a mechanism for efficient resource management will be very significant. Many load balancing algorithms have been already implemented and executed to manage the resources efficiently and adequately. The objective of this paper is to analyze shortcomings of existing algorithms and implement a new algorithm which will give optimized load balancingresult.

Provisioning of Virtual Machines in the Context of an Auto-Scaling Cloud Computing Environment

2020 ◽  
Vol 17 (6) ◽  
pp. 2430-2434
Author(s):  
R. S. Rajput ◽  
Dinesh Goyal ◽  
Rashid Hussain ◽  
Pratham Singh
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Virtual Machines ◽  
Cloud Environment ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Auto Scaling ◽  
Adequate Resource ◽  
Cloud Resources

The cloud computing environment is accomplishing cloud workload by distributing between several nodes or shift to the higher resource so that no computing resource will be overloaded. However, several techniques are used for the management of computing workload in the cloud environment, but still, it is an exciting domain of investigation and research. Control of the workload and scaling of cloud resources are some essential aspects of the cloud computing environment. A well-organized load balancing plan ensures adequate resource utilization. The auto-scaling is a technique to include or terminate additional computing resources based on the scaling policies without involving humans efforts. In the present paper, we developed a method for optimal use of cloud resources by the implementation of a modified auto-scaling feature. We also incorporated an auto-scaling controller for the optimal use of cloud resources.

scholarly journals OLB: A Nature Inspired Approach for Load Balancing in Cloud Computing

2015 ◽  
Vol 15 (4) ◽  
pp. 138-148 ◽  
Author(s):  
B. Mallikarjuna ◽  
P. Venkata Krishna
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Distributed Systems ◽  
Load Balancing ◽  
Virtual Machines ◽  
Simulation Analysis ◽  
Hash Table ◽  
Distributed Hash Table ◽  
Efficient Resource

Abstract Load balancing is treated as one of the important mechanisms for efficient resource allocation in cloud computing. In future there will appear a necessity of fully autonomic distributed systems to address the load balancing issues. With reference to this, we proposed a load balancing mechanism called Osmosis Load Balancing (OLB). OLB works on the principle of osmosis to reschedule the tasks in virtual machines. The solution is based on the Distributed Hash Table (DHT) with a chord overlay mechanism. The Chord overlay is used for managing bio inspired agents and status of the cloud. By simulation analysis, the proposed algorithm has shown better performance in different scenarios, both in heterogeneous and homogeneous clouds.

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