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Virtual-Switching-Aware VM Consolidation in Virtualized Data Centers

Authors: Mingfu Li; Jingping Bi; Zhongcheng Li;

Virtual-Switching-Aware VM Consolidation in Virtualized Data Centers

Abstract

In virtualized data centers, live virtual machine (VM) migration can increase energy efficiency by consolidating VMs on fewer servers. This problem is usually considered as Bin Packing Problem with the server capacity constraints, such as CPU, memory and network bandwidth. In order to minimize the communication traffic in data center network, existing works proposed correlation-aware VM consolidation algorithms. VMs with high inter traffic will be consolidated as close as possible (e.g. Within a physical server). However, the traffic load of virtual switches causes a certain number of CPU cycles of physical servers to move traffic through virtual switches. This increases the risk that VMs running on servers are not allocated enough resource, and consequently reduces VMs' performance. In this work, we conduct experiments to estimate the server CPU overhead caused by virtual switching, and based on the experiment results, we propose virtual-switching-aware VM consolidation algorithm to solve this problem. Experiments on representative data center workloads show that the overhead can occupy 10% to 30% of server's CPU resources. Besides, our algorithm has a sharp decrease of the server capacity violation probability compared with the state-of-the-art baseline.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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