Multiple operating systems on one processor complex
IBM Systems Journal
Disco: running commodity operating systems on scalable multiprocessors
ACM Transactions on Computer Systems (TOCS)
Virtualizing I/O Devices on VMware Workstation's Hosted Virtual Machine Monitor
Proceedings of the General Track: 2002 USENIX Annual Technical Conference
A case for virtual channel processors
NICELI '03 Proceedings of the ACM SIGCOMM workshop on Network-I/O convergence: experience, lessons, implications
Xen and the art of virtualization
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Unmodified device driver reuse and improved system dependability via virtual machines
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Optimizing network virtualization in Xen
ATEC '06 Proceedings of the annual conference on USENIX '06 Annual Technical Conference
High performance VMM-bypass I/O in virtual machines
ATEC '06 Proceedings of the annual conference on USENIX '06 Annual Technical Conference
Performance modeling in industry: a case study on storage virtualization
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 2
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I/O Virtualization provides a convenient way of device sharing among guest domains in a virtualized platform (e.g. Xen). However, with the ever-increasing number and variety of devices, the current model of a centralized driver domain is in question. For example, any optimization in the centralized driver domain for a particular kind of device may not satisfy the conflicting needs of other devices and their usage patterns. This paper has tried to use IO Virtual Machines (IOVMs) as a solution to this problem, specifically to deliver scalable network performance on a multi-core platform. Xen 3 has been extended to support IOVMs for networking and then optimized for a minimal driver domain. Performance comparisons show that by moving the network stack into a separate domain, and optimizing that domain, better efficiency is achieved. Further experiments on different configurations show the flexibility of scheduling across IOVMs and guests to achieve better performance. For example, multiple single-core IOVMs have shown promise as a scalable solution to network virtualization.