A Classification-Based Virtual Machine Placement Algorithm in Mobile Cloud Computing
Yuli Tang,Yao Hu,Lianming Zhang +2 more
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TL;DR: This paper proposes a classification-based virtual machine placement algorithm (CBVMP) for mobile cloud computing, improving VM allocation efficiency and physical resource utilization in large cloud data centers through simulation experiments on CloudSim.
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Abstract: In recent years, cloud computing services based on smart phones and other mobile terminals have been a rapid development. Cloud computing has the advantages of mass storage capacity and high-speed computing power, and it can meet the needs of different types of users, and under the background, mobile cloud computing (MCC) is now booming. In this paper, we have put forward a new classification-based virtual machine placement (CBVMP) algorithm for MCC, and it aims at improving the efficiency of virtual machine (VM) allocation and the disequilibrium utilization of underlying physical resources in large cloud data center. By simulation experiments based on CloudSim cloud platform, the experimental results show that the new algorithm can improve the efficiency of the VM placement and the utilization rate of underlying physical resources.
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Citations
An Efficient Technique for Virtual Machine Clustering and Communications Using Task-Based Scheduling in Cloud Computing
C. Saravanakumar,M. Geetha,S. Manoj Kumar,Sarojini Manikandan,Arun Chokkalingam,K. Srivatsan +5 more
TL;DR: In this paper, the authors proposed a methodology for VM clustering process to place and allocate VM based on the requesting task size with bandwidth level to enhance the efficiency and availability in cloud computing models.
An Efficient Software Defined Data Transmission Scheme Based on Mobile Edge Computing for the Massive IoT Environment.
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Adaptive Resource Management and Provisioning in the Cloud Computing: A Survey of Definitions, Standards and Research Roadmaps
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References
A New Approach to Multi-objective Virtual Machine Placement in Virtualized Data Center
Sinong Wang,Huaxi Gu,Gang Wu +2 more
- 17 Jul 2013
TL;DR: The improved genetic algorithm with local heuristic method and elitism strategy is developed to solve the problem and simulation results show that performance gains can be achieved by the proposed model and algorithm compared to the existing algorithms.
Smart Virtual Machine Placement Using Learning Automata to Reduce Power Consumption in Cloud Data Centers
Hossein Ghiasi,Mostafa Ghobaei-Arani +1 more
TL;DR: This paper proposes a smart virtual machine placement approach using learning automata to reduce power consumption in cloud data centers, balancing energy efficiency with service level agreements, and outperforming existing methods in energy savings.