Power conserving resource allocation scheme with improved QoS to promote green cloud computing

2020 ◽  
Author(s):  
P. Geetha ◽  
C. R. Rene Robin
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Allocation Scheme ◽  
Green Cloud Computing ◽  
Green Cloud ◽  
Resource Allocation Scheme

Smart Configuration and Auto Allocation of Resource in Cloud Data Centers

2018 ◽  
Vol 5 (4) ◽  
pp. 1-23 ◽  
Author(s):  
Merzoug Soltane ◽  
Kazar Okba ◽  
Derdour Makhlouf ◽  
Sean B. Eom
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Data Centers ◽  
Multi Agent Systems ◽  
Energy Aware ◽  
Green Cloud Computing ◽  
Cloud Data ◽  
Operational Costs ◽  
Green Cloud ◽  
Save Energy

Cloud computing is one of emerging computing models that has many advantages. The IT industry is keenly aware of the need for Green Cloud computing solutions that save energy for the environment as well as reduce operational costs. This article presents a new green Cloud Computing framework based on multi agent systems for optimizing resource allocation in data centers (DCs). Our framework based on a new cloud computing architecture that benefits from the combination of the Cloud and agent technologies. DCs hosting Cloud applications need energy-aware resource allocation mechanisms that minimize energy costs and other operational costs. This article offers a logical solution to manage physical and virtual resources in smarter data center.

scholarly journals Efficient Task Allocation Based on Green Computing in Private Cloud

2019 ◽  
Vol 2 (1) ◽  
pp. 68-76
Author(s):  
Neeraj single
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Global Warming ◽  
Cloud Provider ◽  
User Requirements ◽  
New Paradigm ◽  
Research Issues ◽  
Green Cloud Computing ◽  
Computing Resource ◽  
Green Cloud

Cloud computing is a rapidly emerging new paradigm for delivering computing as a service. There are many research issues in cloud computing. Resource allocation is one of the challenging tasks in cloud environment. The main aim of resource allocation to reduce the infrastructure cost associated with companies. The resources offered in the cloud are probably heterogeneous and extremely dynamic. Due to this dynamic access, load balancing of jobs required. Cloud computing resource allocation should be elastic and intelligent, based on application demand and user requirements [1].Green cloud computing is a trend which has become popular with the emergence of internet driven services in every field of life. It refers to the prospective environmental advantages that computer based internet services can guarantee to the environment, by processing huge amount of data and information from collective resources pool.load balancing in an efficient way so that the resource utilization can be maximized and the energy consumption of the data centre could be minimized that can further result in reducing global warming. We have concluded the parameters that should be analysed and improved that will result in reduction of global warming and will increase the profits of cloud provider and the client. Cloud computing resource allocation should be elastic and intelligent, based on application demand and user requirements. Green cloud computing is a trend which has become popular with the emergence of internet driven services in every field of life

scholarly journals Scheduling Fair Resource Allocation Policies for Cloud Computing through Flow Control

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1348 ◽  
Author(s):  
Stavros Souravlas ◽  
Stefanos Katsavounis
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Flow Control ◽  
Resource Utilization ◽  
Short Paper ◽  
Allocation Scheme ◽  
Through Flow ◽  
Resource Requirements ◽  
Efficient Resource ◽  
Resource Allocation Scheme

In this short paper, we discuss the problem of resource allocation for cloud computing. The cloud provides a variety of resources for users based on their requirements. Thus, one of the main issues in cloud computing is to design an efficient resource allocation scheme. Each job generated by a user in the cloud has some resource requirements. In this work, we propose a resource allocation method which aims at maximizing the resource utilization and distributing the system’s resources in a fast and fair way, by controlling the flow according to the resources available and by analyzing the dominant demands of each job. Moreover, by parallelizing the computations required, the runtime of the proposed strategy increases linearly as the number of jobs N increases. Here, we present some initial experimental results for small sets of users, that have shown that our strategy allocates the available resources among user jobs in a fair manner, while increasing the overall utilization of each resource.

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