A Classification-Based Virtual Machine Placement Algorithm in Mobile Cloud Computing
Yuli Tang,Yao Hu,Lianming Zhang +2 more
3
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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References
Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing
TL;DR: An architectural framework and principles for energy-efficient Cloud computing are defined and the proposed energy-aware allocation heuristics provision data center resources to client applications in a way that improves energy efficiency of the data center, while delivering the negotiated Quality of Service (QoS).
2.8K
Heterogeneity in Mobile Cloud Computing: Taxonomy and Open Challenges
TL;DR: This paper defines MCC, explains its major challenges, discusses heterogeneity in convergent computing and networking, and divides it into two dimensions, namely vertical and horizontal.
665
Mobile Cloud Computing: A Survey, State of Art and Future Directions
TL;DR: The applicability of MCC in various domains including mobile learning, commerce, health/wellness and social medias is illustrated, and research gaps covering critical aspects of how MCC can be realized and effectively utilized at scale are identified.
407
Optimal virtual machine placement across multiple cloud providers
Sivadon Chaisiri,Bu-Sung Lee,Dusit Niyato +2 more
- 01 Dec 2009
TL;DR: An optimal virtual machine placement (OVMP) algorithm can minimize the cost spending in each plan for hosting virtual machines in a multiple cloud provider environment under future demand and price uncertainty.
393
A scalable application placement controller for enterprise data centers
Chunqiang Tang,Malgorzata Steinder,Mike Spreitzer,Giovanni Pacifici +3 more
- 08 May 2007
TL;DR: This paper proposes a new algorithm that can produce within 30seconds high-quality solutions for hard placement problems with thousands of machines and thousands of applications, and has been implemented and adopted in a leading commercial middleware product for managing the performance of Web applications.