Network performance isolation for virtual machines

Abstract

Cloud computing is a new computing paradigm that aims to transform computing

services into a utility, just as providing electricity in a “pay-as-you-go”

manner. Data centers are increasingly adopting virtualization technology for the

purpose of server consolidation, flexible resource management and better fault

tolerance. Virtualization-based cloud services host networked applications in virtual

machines (VMs), with each VM provided the desired amount of resources

using resource isolation mechanisms.

Effective network performance isolation is fundamental to data centers, which

offers significant benefit of performance predictability for applications. This research

is application-driven. We study how network performance isolation can be

achieved for latency-sensitive cloud applications. For media streaming applications,

network performance isolation means both predicable network bandwidth

and low-jittered network latency. The current resource sharing methods for VMs

mainly focus on resource proportional share, whereas ignore the fact that I/O latency

in VM-hosted platforms is mostly related to resource provisioning rate. The

resource isolation with only quantitative promise does not sufficiently guarantee

performance isolation. Even the VM is allocated with adequate resources such as

CPU time and network bandwidth, problems such as network jitter (variation in

packet delays) can still happen if the resources are provisioned at inappropriate

moments. So in order to achieve performance isolation, the problem is not only

how many/much resources each VM gets, but more importantly whether the resources are provisioned in a timely manner. How to guarantee both requirements

to be achieved in resource allocation is challenging.

This thesis systematically analyzes the causes of unpredictable network latency

in VM-hosted platforms, with both technical discussion and experimental

illustration. We identify that the varied network latency is jointly caused by

VMM CPU scheduler and network traffic shaper, and then address the problem

in these two parts. In our solutions, we consider the design goals of resource

provisioning rate and resource proportionality as two orthogonal dimensions. In

the hypervisor, a proportional share CPU scheduler with soft real-time support

is proposed to guarantee predictable scheduling delay; in network traffic shaper,

we introduce the concept of smooth window to smooth packet delay and apply

closed-loop feedback control to maintain network bandwidth consumption.

The solutions are implemented in Xen 4.1.0 and Linux 2.6.32.13, which are

both the latest versions when this research was conducted. Extensive experiments

have been carried out using both real-life applications and low-level benchmarks.

Testing results show that the proposed solutions can effectively guarantee network

performance isolation, by achieving both predefined network bandwidth and low-jittered

network latency.