A Survey on the Use of Preferences for Virtual Machine Placement in Cloud Data Centers
July 17, 2019 ยท The Cartographer ยท ๐ ACM Computing Surveys
"No code URL or promise found in abstract"
"Title-pattern auto-detect: A Survey on the Use of Preferences for Virtual Machine Placement in Cloud Data Centers"
Evidence collected by the PWNC Scanner
Authors
Abdulaziz Alashaikh, Eisa Alanazi, Ala Al-Fuqaha
arXiv ID
1907.07778
Category
cs.DC: Distributed Computing
Cross-listed
cs.AI,
cs.NI
Citations
23
Venue
ACM Computing Surveys
Last Checked
2 days ago
Abstract
With the rapid development of virtualization techniques, cloud data centers allow for cost effective, flexible, and customizable deployments of applications on virtualized infrastructure. Virtual machine (VM) placement aims to assign each virtual machine to a server in the cloud environment. VM Placement is of paramount importance to the design of cloud data centers. Typically, VM placement involves complex relations and multiple design factors as well as local policies that govern the assignment decisions. It also involves different constituents including cloud administrators and customers that might have disparate preferences while opting for a placement solution. Thus, it is often valuable to not only return an optimized solution to the VM placement problem but also a solution that reflects the given preferences of the constituents. In this paper, we provide a detailed review on the role of preferences in the recent literature on VM placement. We further discuss key challenges and identify possible research opportunities to better incorporate preferences within the context of VM placement.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Distributed Computing
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
Reproducing GW150914: the first observation of gravitational waves from a binary black hole merger
R.I.P.
๐ป
Ghosted
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
R.I.P.
๐ป
Ghosted
Efficient Architecture-Aware Acceleration of BWA-MEM for Multicore Systems
R.I.P.
๐ป
Ghosted
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
R.I.P.
๐ป
Ghosted