Quantifying and improving I/O predictability in virtualized systems

Cheng Li, Inigo Goiri, Abhishek Bhattacharjee, Ricardo Bianchini, Thu D. Nguyen

Research output: Contribution to journalConference articlepeer-review

8 Scopus citations


Virtualization enables the consolidation of virtual machines (VMs) to increase the utilization of physical servers in Infrastructure-as-a-Service (IaaS) cloud providers. However, our experience shows that storage I/O performance varies wildly in the face of consolidation. Since many users may desire consistent performance, we argue that IaaS providers should offer a class of predictable-performance service in addition to existing (predictability- oblivious) services. Thus, we propose VirtualFence, a storage system that provides predictable VM performance. VirtualFence uses three main techniques: (1) non-work-conserving time-division I/O scheduling, (2) a small solid-state (SSD) cache in front of a much larger hard disk drive (HDD), and (3) space-partitioning of both the SSD cache and the HDD. Our evaluation shows that VirtualFence improves predictability significantly, while allowing cloud providers to reach any desired compromise between predictability and performance.

Original languageEnglish (US)
Article number6550269
Pages (from-to)93-98
Number of pages6
JournalIEEE International Workshop on Quality of Service, IWQoS
StatePublished - 2013
Event2013 IEEE/ACM 21st International Symposium on Quality of Service, IWQoS 2013 - Montreal, QC, Canada
Duration: Jun 3 2013Jun 4 2013

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


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