scholarly journals WITHDRAWN: A Dynamic Energy-efficient Resource Management Scheme and Performance Optimization in Cloud Data Centers

2020 ◽  
pp. 100211
Author(s):  
Yu Cui ◽  
Shunfu Jin ◽  
Wuyi Yue
Keyword(s):  
Resource Management ◽  
Performance Optimization ◽  
Energy Efficient ◽  
Data Centers ◽  
Cloud Data ◽  
Management Scheme ◽  
Efficient Resource ◽  
Cloud Data Centers ◽  
And Performance

scholarly journals Performance Optimization of Cloud Data Centers with a Dynamic Energy-Efficient Resource Management Scheme

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Yu Cui ◽  
Shunfu Jin ◽  
Wuyi Yue ◽  
Yutaka Takahashi
Keyword(s):  
Resource Management ◽  
Performance Optimization ◽  
Energy Efficient ◽  
Data Centers ◽  
Network Resource ◽  
System Cost ◽  
Cloud Data ◽  
Management Scheme ◽  
Efficient Resource ◽  
Sleep Mechanism

As an advanced network calculation mode, cloud computing is becoming more and more popular. However, with the proliferation of large data centers hosting cloud applications, the growth of energy consumption has been explosive. Surveys show that a remarkable part of the large energy consumed in data center results from over-provisioning of the network resource to meet requests during peak demand times. In this paper, we propose a solution to this problem by constructing a dynamic energy-efficient resource management scheme. As a way of saving energy as well as maintaining cloud user’s quality of experience, the scheme presents a multitier cloud architecture by configuring physical machines (PMs) into two pools: a hot (running) pool and a warm (turned on, but in dynamic sleep) pool. Each PM is configured with a resource search engine (RSE) that finds an available virtual machine (VM) for the request, and a synchronous sleep mechanism is introduced to the warm pool. To analyze the end-to-end performance of the cloud system’s service with the proposed scheme, we establish a hybrid queueing system composed of three stochastic submodels by using a matrix-geometric solution. Accordingly, the average latency of requests and the energy-saving rate of the system are derived. Through numerical results, we show the influence of the synchronous sleep mechanism on the system performance. Moreover, from the perspective of economics, we build a system cost function to study the trade-off between different performance measures. An improved Salp Swarm Algorithm (SSA) is presented to minimize the system cost and optimize the sleep parameter.

Service level agreement based energy-efficient resource management in cloud data centers

2014 ◽  
Vol 40 (5) ◽  
pp. 1621-1633 ◽  
Author(s):  
Yongqiang Gao ◽  
Haibing Guan ◽  
Zhengwei Qi ◽  
Tao Song ◽  
Fei Huan ◽  
...  
Keyword(s):  
Resource Management ◽  
Energy Efficient ◽  
Data Centers ◽  
Service Level Agreement ◽  
Service Level ◽  
Cloud Data ◽  
Efficient Resource ◽  
Cloud Data Centers

Penalty-aware and cost-efficient resource management in cloud data centers

2016 ◽  
Vol 30 (8) ◽  
pp. e3179 ◽  
Author(s):  
AA Rahmanian ◽  
GH Dastghaibyfard ◽  
H Tahayori
Keyword(s):  
Resource Management ◽  
Data Centers ◽  
Cloud Data ◽  
Efficient Resource ◽  
Cloud Data Centers ◽  
Cost Efficient
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