Online Allocation of Virtual Machines in a Distributed Cloud

2017 ◽  
Vol 25 (1) ◽  
pp. 238-249 ◽  
Author(s):  
Fang Hao ◽  
Murali Kodialam ◽  
T. V. Lakshman ◽  
Sarit Mukherjee
Keyword(s):  
Virtual Machines ◽  
Distributed Cloud

Clustering based virtual machines placement in distributed cloud computing

2017 ◽  
Vol 66 ◽  
pp. 1-10 ◽  
Author(s):  
Jiangtao Zhang ◽  
Xuan Wang ◽  
Hejiao Huang ◽  
Shi Chen
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Distributed Cloud

Optimal Dynamic Placement of Virtual Machines in Geographically Distributed Cloud Data Centers

2017 ◽  
Vol 26 (03) ◽  
pp. 1750001 ◽  
Author(s):  
Hana Teyeb ◽  
Nejib Ben Hadj-Alouane ◽  
Samir Tata ◽  
Ali Balma
Keyword(s):  
Virtual Machines ◽  
Time Frame ◽  
Cloud Infrastructure ◽  
Vm Placement ◽  
Vm Migration ◽  
Cloud Data ◽  
Geographically Distributed ◽  
Optimal Dynamic ◽  
And Migration ◽  
Distributed Cloud

In geo-distributed cloud systems, a key challenge faced by cloud providers is to optimally tune and configure the underlying cloud infrastructure. An important problem in this context, deals with finding an optimal virtual machine (VM) placement, minimizing costs, while at the same time, ensuring good system performance. Moreover, due to the fluctuations of demand and traffic patterns, it is crucial to dynamically adjust the VM placement scheme over time. It should be noted that most of the existing studies, however, dealt with this problem either by ignoring its dynamic aspect or by proposing solutions that are not suitable for a geographically distributed cloud infrastructure. In this paper, exact as well as heuristic solutions based on Integer Linear programming (ILP) formulations are proposed. Our work focuses also on the problem of scheduling the VM migration by finding the best migration sequence of intercommunicating VMs that minimizes the resulting traffic on the backbone network. The proposed algorithms execute within a reasonable time frame to readjust VM placement scheme according to the perceived demand. Our aim is to use VM migration as a tool for dynamically adjusting the VM placement scheme while minimizing the network traffic generated by VM communication and migration. Finally, we demonstrate the effectiveness of our proposed algorithms by performing extensive experiments and simulation.

scholarly journals Heuristic-based Approach for Dynamic Consolidation of Software Licenses in Cloud Data Centers

2021 ◽  
Vol 13 (6) ◽  
pp. 1-12
Author(s):  
Leila Helali ◽  
◽  
Mohamed Nazih Omri
Keyword(s):  
Cloud Computing ◽  
Data Centers ◽  
Virtual Machines ◽  
Heuristic Algorithms ◽  
Energy Aware ◽  
Computing Systems ◽  
Cloud Data ◽  
Software Licenses ◽  
Cloud Data Centers ◽  
Distributed Cloud

Since its emergence, cloud computing has continued to evolve thanks to its ability to present computing as consumable services paid by use, and the possibilities of resource scaling that it offers according to client’s needs. Models and appropriate schemes for resource scaling through consolidation service have been considerably investigated,mainly, at the infrastructure level to optimize costs and energy consumption. Consolidation efforts at the SaaS level remain very restrained mostly when proprietary software are in hand. In order to fill this gap and provide software licenses elastically regarding the economic and energy-aware considerations in the context of distributed cloud computing systems, this work deals with dynamic software consolidation in commercial cloud data centers 𝑫𝑺𝟑𝑪. Our solution is based on heuristic algorithms and allows reallocating software licenses at runtime by determining the optimal amount of resources required for their execution and freed unused machines. Simulation results showed the efficiency of our solution in terms of energy by 68.85% savings and costs by 80.01% savings. It allowed to free up to 75% physical machines and 76.5% virtual machines and proved its scalability in terms of average execution time while varying the number of software and the number of licenses alternately.

Scheduling Strategies for Business Process Applications in Cloud Environments

2013 ◽  
Vol 5 (4) ◽  
pp. 65-78 ◽  
Author(s):  
Kahina Bessai ◽  
Samir Youcef ◽  
Ammar Oulamara ◽  
Claude Godart ◽  
Selmin Nurcan
Keyword(s):  
Business Processes ◽  
Virtual Machines ◽  
Cloud Infrastructure ◽  
On Demand ◽  
Computing Paradigm ◽  
Elastic Computing ◽  
Cloud Environments ◽  
Scheduling Strategies ◽  
The Many ◽  
Distributed Cloud

The Cloud computing paradigm is adopted for its several advantages like reduction of cost incurred when using a set of resources. However, despite the many proven benefits of using a Cloud infrastructure to run business processes, it is still faced with a major problem that can compromise its success: the lack of guidance for choosing between multiple offerings. Moreover, when running business processes it is difficult to automate all tasks and several objectives often conflicting must be taken into account. For this, the authors propose a set of scheduling strategies for business processes in Cloud contexts. More precisely, the authors propose three bi-criteria complementary approaches for scheduling business processes on distributed Cloud resources while taking into account its elastic computing characteristic that allows users to allocate and release compute resources (virtual machines) on-demand and its business model based on pay as you go. Therefore, it is reasonable to assume that the number of virtual machine is infinite while the number of human resources is finite. Experiment results demonstrate that the proposed approaches present good performances.

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