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Title:
CIVSched: A communication-aware inter-VM scheduling technique for decreased network latency between co-located VMs
Author: Guan, Bei (1) ; Wu, Jingzheng (1) ; Wang, Yongji (1) ; Khan, Samee U. (2)
Corresponding Author: Guan, Bei
Source: IEEE Transactions on Cloud Computing
Issued Date: 2014
Volume: 2, Issue:3, Pages:320-332
Indexed Type: EI
Department: (1) Institute of Software, Chinese Academy of Sciences, Beijing, China; (2) Department of Electrical and Computer Engineering, North Dakota State University, Fargo; ND, United States
Abstract: Server consolidation in cloud computing environments makes it possible for multiple servers or desktops to run on a single physical server for high resource utilization, low cost, and reduced energy consumption. However, the scheduler in the virtual machine monitor (VMM), such as Xen credit scheduler, is agnostic about the communication behavior between the guest operating systems (OS). The aforementioned behavior leads to increased network communication latency in consolidated environments. In particular, the CPU resources management has a critical impact on the network latency between co-located virtual machines (VMs) when there are CPU- and I/O-intensive workloads running simultaneously. This paper presents the design and implementation of a communication-aware inter-VM scheduling (CIVSched) technique that takes into account the communication behavior betweeninter-VMs running on the same virtualization platform. The CIVSched technique inspects the network packets transmitted between local co-resident domains to identify the target VM and process that will receive the packets. Thereafter, the target VM and process are preferentially scheduled by the VMM and the guest OS. The cooperation of these two schedulers makes the network packets to be timely received by the target application. Experimental results on the Xen virtualization platform depict that the CIVSched technique can reduce the average response time of network traffic by approximately 19 percent for the highly consolidated environment, while keeping the inherent fairness of the VMM scheduler.
English Abstract: Server consolidation in cloud computing environments makes it possible for multiple servers or desktops to run on a single physical server for high resource utilization, low cost, and reduced energy consumption. However, the scheduler in the virtual machine monitor (VMM), such as Xen credit scheduler, is agnostic about the communication behavior between the guest operating systems (OS). The aforementioned behavior leads to increased network communication latency in consolidated environments. In particular, the CPU resources management has a critical impact on the network latency between co-located virtual machines (VMs) when there are CPU- and I/O-intensive workloads running simultaneously. This paper presents the design and implementation of a communication-aware inter-VM scheduling (CIVSched) technique that takes into account the communication behavior betweeninter-VMs running on the same virtualization platform. The CIVSched technique inspects the network packets transmitted between local co-resident domains to identify the target VM and process that will receive the packets. Thereafter, the target VM and process are preferentially scheduled by the VMM and the guest OS. The cooperation of these two schedulers makes the network packets to be timely received by the target application. Experimental results on the Xen virtualization platform depict that the CIVSched technique can reduce the average response time of network traffic by approximately 19 percent for the highly consolidated environment, while keeping the inherent fairness of the VMM scheduler.
Language: 英语
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/17008
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Guan, Bei ,Wu, Jingzheng ,Wang, Yongji ,et al. CIVSched: A communication-aware inter-VM scheduling technique for decreased network latency between co-located VMs[J]. IEEE Transactions on Cloud Computing,2014-01-01,2(3):320-332.
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