Using Network Knowledge to Improve Workload Performance in Virtualized Data Centers

Author

Erickson, David ; Heller, Ben ; McKeown, N. ; Rosenblum, Mendel

Author_Institution

Stanford Univ., Stanford, CA, USA

fYear

2014

fDate

11-14 March 2014

Firstpage

185

Lastpage

194

Abstract

The scale and expense of modern data centers motivates running them as efficiently as possible. This paper explores how virtualized data center performance can be improved when network traffic and topology data informs VM placement. Our practical heuristics, tested on network-heavy, scale-out workloads in an 80 server cluster, improve overall performance by up to 70% compared to random placement in a multi-tenant configuration.

Keywords

computer centres; computer network performance evaluation; network servers; telecommunication network topology; telecommunication traffic; virtual machines; virtualisation; VM placement; network knowledge; network topology data; network traffic; network-heavy scale-out workloads; server cluster; virtual machines; virtualized data center performance; workload performance improvement; Bandwidth; Heuristic algorithms; Knowledge engineering; Network topology; Optimization; Servers; Switches; algorithms; beacon; data center; migration; network; openflow; optimization; performance; sdn; software defined networking; virtualization; virtue;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud Engineering (IC2E), 2014 IEEE International Conference on

Conference_Location

Boston, MA

Type

conf

DOI

10.1109/IC2E.2014.81

Filename

6903473