scholarly journals Energy-Aware VM placement based on intra-balanced resource allocation in data centers

Author(s):  
Imene El-Taani ◽  
Mohand-Cherif Boukala ◽  
Samia Bouzefrane
2016 ◽  
Vol 27 (12) ◽  
pp. 3646-3658 ◽  
Author(s):  
Bo Yang ◽  
Zhiyong Li ◽  
Shaomiao Chen ◽  
Tao Wang ◽  
Keqin Li

2018 ◽  
Vol 173 ◽  
pp. 03092
Author(s):  
Bo Li ◽  
Yun Wang

Virtual machine placement is the process of selecting the most suitable server in large cloud data centers to deploy newly-created VMs. Traditional load balancing or energy-aware VM placement approaches either allocate VMs to PMs in centralized manner or ignore PM’s cost-capacity ratio to implement energy-aware VM placement. We address these two issues by introducing a distributed VM placement approach. A auction-based VM placement algorithm is devised for help VM to find the most suitable server in large heterogeneous cloud data centers. Our algorithm is evaluated by simulation. Experimental results show two major improvements over the existing approaches for VM placement. First, our algorithm efficiently balances the utilization of multiple types of resource by minimizing the amount of physical servers used. Second, it reduces system cost compared with existing approaches in heterogeneous environment.


2018 ◽  
Vol 5 (4) ◽  
pp. 1-23 ◽  
Author(s):  
Merzoug Soltane ◽  
Kazar Okba ◽  
Derdour Makhlouf ◽  
Sean B. Eom

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.


Author(s):  
Eugen Feller ◽  
Louis Rilling ◽  
Christine Morin

With increasing numbers of energy hungry data centers, energy conservation has now become a major design constraint for current and future Infrastructure-as-a-Service (IaaS) cloud providers. In order to efficiently manage such large-scale environments, three important properties have to be fulfilled by the management frameworks: (1) scalability, (2) fault-tolerance, and (3) energy-awareness. However, the scalability and fault tolerance capabilities of existing open-source IaaS cloud management frameworks are limited. Moreover, they are far from being energy-aware. This chapter first surveys existing efforts on building IaaS platforms. This includes both, system architectures and energy-aware virtual machine (VM) placement algorithms. Afterwards, it describes the architecture and implementation of a novel scalable, fault-tolerant, and energy-aware VM manager called Snooze. Finally, a nature-inspired energy-aware VM placement approach based on the Ant Colony Optimization is introduced.


2019 ◽  
Vol 7 (4) ◽  
pp. 1109-1123 ◽  
Author(s):  
Gagangeet Singh Aujla ◽  
Mukesh Singh ◽  
Neeraj Kumar ◽  
Albert Y. Zomaya

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