Energy-Efficient Resource Provisioning with SLA Consideration on Cloud Computing

2012 ◽  
Author(s):  
Jian-Sheng Liao ◽  
Chi-Chung Chang ◽  
Yao-Lun Hsu ◽  
Xiao-Wei Zhang ◽  
Kuan-Chou Lai ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Energy Efficient ◽  
Resource Provisioning ◽  
Efficient Resource

scholarly journals Research on Energy-Efficient Resource Provisioning System for Cloud Datacenters

2019 ◽  
Vol 8 (4) ◽  
pp. 12529-12534
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
Energy Efficient ◽  
Resource Provisioning ◽  
Heuristic Methods ◽  
The Real ◽  
Efficient Resource ◽  
Cloud Framework ◽  
Asset Distribution ◽  
Np Complete

Cloud computing frameworks are intended to help the availability and sending of different assistance situated applications by the clients. Distributed computing administrations are made accessible through the server firms or server farms. These assets are the real wellspring of the power utilization in server farms alongside cooling and cooling gear. In addition the vitality utilization in the cloud is corresponding to the asset usage and server farms are nearly the world's most noteworthy purchasers of power. The asset distribution issue in a nature of NP-complete, which requiring the improvement of heuristic systems to take care of the asset allotment issue in a distributed computing condition. The multifaceted nature of the asset distribution issue increments with the size of cloud framework and winds up hard to settle successfully. The exponential arrangement space for the asset designation issue can look through utilizing heuristic methods to acquire a problematic arrangement at the satisfactory time.

QoS Based Efficient Resource Allocation and Scheduling in Cloud Computing

2019 ◽  
Vol 15 (4) ◽  
pp. 13-29
Author(s):  
Harvinder Chahal ◽  
Anshu Bhasin ◽  
Parag Ravikant Kaveri
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Resource Provisioning ◽  
Cloud Environment ◽  
Allocation Decision ◽  
Research Article ◽  
Large Pool ◽  
Efficient Resource ◽  
Algorithm Implementation

The Cloud environment is a large pool of virtually available resources that perform thousands of computational operations in real time for resource provisioning. Allocation and scheduling are two major pillars of said provisioning with quality of service (QoS). This involves complex modules such as: identification of task requirement, availability of resource, allocation decision, and scheduling operation. In the present scenario, it is intricate to manage cloud resources, as Service provider aims to provide resources to users on productive cost and time. In proposed research article, an optimized technique for efficient resource allocation and scheduling is presented. The proposed policy used heuristic based, ant colony optimization (ACO) for well-ordered allocation. The suggested algorithm implementation done using simulation, shows better results in terms of cost, time and utilization as compared to other 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.

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