Name
Abstract | ||
|---|---|---|
Data centers are increasingly employing virtualization and consolidation as a means to support a large number of disparate applications running simultaneously on server platforms. However, server platforms are still being designed and evaluated based on performance modeling of a single highly parallel application or a set of homogenous work-loads running simultaneously. Since most future datacenters are expected to employ server virtualization, this paper takes a look at the challenges of modeling virtual machine (VM) performance on a datacenter server. Based on vConsolidate (a server virtualization benchmark) and latest multi-core servers, we show that the VM modeling challenge requires addressing three key problems: (a) modeling the contention of visible resources (cores, memory capacity, I/O devices, etc), (b) modeling the contention of invisible resources (shared microarchitecture resources, shared cache, shared memory bandwidth, etc) and (c) modeling overheads of virtual machine monitor (or hypervisor) implementation. We take a first step to addressing this problem by describing a VM performance modeling approach and performing a detailed case study based on the vConsolidate benchmark. We conclude by outlining outstanding problems for future work. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1710115.1710126 | SIGMETRICS Performance Evaluation Review |
Keywords | Field | DocType |
virtualization,shared cache,cmp,virtual machine performance,measurement,performance analysis,shared memory bandwidth,performance modeling,server virtualization,server virtualization benchmark,modeling,servers,modeling.,datacenter server,server platform,vm modeling challenge,vm performance modeling approach,consolidation,latest multi-core server,virtual machine,resource sharing,shared memory,virtual machine monitor,data center | Virtualization,Hardware virtualization,Virtual machine,Shared memory,Computer science,Server,Hypervisor,Data diffusion machine,Real-time computing,Full virtualization,Operating system,Distributed computing | Journal |
Volume | Issue | Citations |
37 | 3 | 31 |
PageRank | References | Authors |
1.46 | 12 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Omesh Tickoo | 1 | 389 | 31.58 |
| Ravishankar K. Iyer | 2 | 1119 | 75.72 |
| Ramesh Illikkal | 3 | 481 | 33.98 |
| Don Newell | 4 | 512 | 32.67 |