Towards Optimized Security-aware (O-Sec) VM Placement Algorithms

2017 ◽  
Author(s):  
Motlatsi i Isaac Thulo ◽  
J. H. P. Eloff
Keyword(s):  
Vm Placement ◽  
Placement Algorithms

scholarly journals CloudBench: an integrated evaluation of VM placement algorithms in clouds

2020 ◽  
Vol 76 (9) ◽  
pp. 7047-7080 ◽  
Author(s):  
Mario A. Gomez-Rodriguez ◽  
Victor J. Sosa-Sosa ◽  
Jesus Carretero ◽  
Jose Luis Gonzalez
Keyword(s):  
Vm Placement ◽  
Placement Algorithms

scholarly journals Putting the Next 500 VM Placement Algorithms to the Acid Test: The Infrastructure Provider Viewpoint

2019 ◽  
Vol 30 (1) ◽  
pp. 204-217 ◽  
Author(s):  
Adrien Lebre ◽  
Jonathan Pastor ◽  
Anthony Simonet ◽  
Mario Sudholt
Keyword(s):  
Vm Placement ◽  
Placement Algorithms ◽  
Acid Test

scholarly journals Efficient virtual machine placement algorithms for consolidation in cloud data centers

2020 ◽  
Vol 17 (1) ◽  
pp. 29-50
Author(s):  
Loiy Alsbatin ◽  
Gürcü Öz ◽  
Ali Ulusoy
Keyword(s):  
Virtual Machine ◽  
Service Level Agreement ◽  
Energy Performance ◽  
Service Level ◽  
Vm Placement ◽  
Cloud Data ◽  
Successful Approach ◽  
Cloud Data Centers ◽  
Placement Algorithms ◽  
Best Fit

Dynamic Virtual Machine (VM) consolidation is a successful approach to improve the energy efficiency and the resource utilization in cloud environments. Consequently, optimizing the online energy-performance tradeoff directly influences quality of service. In this study, algorithms named as CPU Priority based Best-Fit Decreasing (CPBFD) and Dynamic CPU Priority based Best-Fit Decreasing (DCPBFD) are proposed for VM placement. A number of VM placement algorithms are implemented and compared with the proposed algorithms. The algorithms are evaluated through simulations with real-world workload traces and it is shown that the proposed algorithms outperform the known algorithms. The simulation results clearly show that CPBFD and DCPBFD provide the least service level agreement violations, least VM migrations, and efficient energy consumption.

A Study for VM Placement Schemes in Cloud

2017 ◽  
Vol 7 (8) ◽  
pp. 208
Author(s):  
Ramandeep Kaur ◽  
Navpreet Kaur
Keyword(s):  
Cloud Computing ◽  
Reaction Time ◽  
Task Scheduling ◽  
Specific Time ◽  
Due Date ◽  
Vm Placement ◽  
Time Task ◽  
Wide Range ◽  
The Web

The cloud computing can be essentially expressed as aconveyance of computing condition where distinctive assets are conveyed as a support of the client or different occupants over the web. The task scheduling basically concentrates on improving the productive use of assets and henceforth decrease in task fruition time. Task scheduling is utilized to allot certain tasks to specific assets at a specific time occurrence. A wide range of systems has been exhibited to take care of the issues of scheduling of various tasks. Task scheduling enhances the productive use of asset and yields less reaction time with the goal that the execution of submitted tasks happens inside a conceivable least time. This paper talks about the investigation of need, length and due date based task scheduling calculations utilized as a part of cloud computing.

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