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The hybrid scheduling framework for virtual machine systems
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ACM/Usenix International Conference On Virtual Execution Environments archive
Proceedings of the 2009 ACM SIGPLAN/SIGOPS international conference on Virtual execution environments table of contents
Washington, DC, USA
SESSION: Hybrid techniques table of contents
Pages 111-120  
Year of Publication: 2009
ISBN:978-1-60558-375-4
Authors
Chuliang Weng  Shanghai Jiao Tong University, Shanghai, China
Zhigang Wang  Shanghai Jiao Tong University, Shanghai, China
Minglu Li  Shanghai Jiao Tong University, Shanghai, China
Xinda Lu  Shanghai Jiao Tong University, Shanghai, China
Sponsors
ACM: Association for Computing Machinery
SIGPLAN: ACM Special Interest Group on Programming Languages
SIGOPS: ACM Special Interest Group on Operating Systems
Publisher
ACM  New York, NY, USA
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ABSTRACT

The virtualization technology makes it feasible that multiple guest operating systems run on a single physical machine. It is the virtual machine monitor that dynamically maps the virtual CPU of virtual machines to physical CPUs according to the scheduling strategy. The scheduling strategy in Xen schedules virtual CPUs of a virtual machines asynchronously while guarantees the proportion of the CPU time corresponding to its weight, maximizing the throughput of the system. However, this scheduling strategy may deteriorate the performance when the virtual machine is used to execute the concurrent applications such as parallel programs or multithreaded programs. In this paper, we analyze the CPU scheduling problem in the virtual machine monitor theoretically, and the result is that the asynchronous CPU scheduling strategy will waste considerable physical CPU time when the system workload is the concurrent application. Then, we present a hybrid scheduling framework for the CPU scheduling in the virtual machine monitor. There are two types of virtual machines in the system: the high-throughput type and the concurrent type. The virtual machine can be set as the concurrent type when the majority of its workload is concurrent applications in order to reduce the cost of synchronization. Otherwise, it is set as the high-throughput type as the default. Moreover, we implement the hybrid scheduling framework based on Xen, and we will give a description of our implementation in details. At last, we test the performance of the presented scheduling framework and strategy based on the multi-core platform, and the experiment result indicates that the scheduling framework and strategy is feasible to improve the performance of the virtual machine system.


REFERENCES

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1
P. Gum. System/370 extended architecture: Facilities for virtual machines. IBM Journal of Research and Development, 27(6):530--544, 1983.
 
2
3
4
 
5
Microsoft Corporation. Microsoft virtual server 2005. http://www.microsoft.com/windowsserversystem/virtualserver/default.mspx.
6
 
7
A. Whitaker, M. Shaw, and S. Gribble. Denali: Lightweight virtual machines for distributed and networked applications. In Proceedings of the USENIX Annual Technical Conference, October 2002.
 
8
 
9
10
 
11
I. Leslie, D. Mcauley, R. Black, T. Roscoe, P. Barham, D. Evers, R. Fairbairns, and E. Hyden. The design and implementation of an operating system to support distributed multimedia applications. IEEE Journal of Selected Areas in Communications, 14(7):1280--1297, 1996.
 
12
Credit Scheduler. http://wiki.xensource.com/xenwiki/credit scheduler.
 
13
Stanford Parallel Applications for Shared Memory (SPLASH). http://www-flash.stanford.edu/splash/.
14
 
15
httperf. http://www.hpl.hp.com/research/linux/httperf/.
 
16
 
17
S. Leffler, M. McKusick, and M. Karels. The Design and Implementation of the 4.3 BSD Unix Operating System. Addison-Wesley, 1988.
18
 
19
G. Henry. The fair share scheduler. AT&T Bell Labs Technical Journal, 63(8):1945--1957, 1984.
 
20
R. Essick. An event based fair share scheduler. In Proceedings of the Winter USENIX Conference, pages 147--161, 1990.
 
21
 
22
D. Feitelson, L. Rudolph and U. Schwiegelshohn. Parallel job scheduling -- a status report. In Proceedings of the 10th Workshop on Job Scheduling Strategies for Parallel Processing, pages 1--16, 2004.
 
23
 
24
E. Shmueli and D. Feitelson. Backfilling with lookahead to optimize the performance of parallel job scheduling. In Proceedings of the 9th Workshop on Job Scheduling Strategies for Parallel Processing, pages 228--251, 2003.
 
25
J. Ousterhout. Scheduling techniques for concurrent systems. In Proceedings of Third International Conference on Distributed Computing Systems (ICDCS), pages 22--30, 1982.
 
26
D. Feitelson and L. Rudolph. Gang scheduling performance benefits for fine-grain synchronization. Journal of Parallel and Distributed Computing, 16(4):306--318, 1992.
 
27
 
28
 
29
 
30
VMWARE. Performance tuning best practices for ESX server 3, 2007. http://www.vmware.com/pdf/vi_performance_tuning.pdf.
 
31
VMWARE. Best practices using vmware virtual SMP, 2005. http://www.vmware.com/pdf/vsmp_best_practices.pdf.
32
33
34
 
35
 
36
H. Raj and K. Schwan. Implementing a scalable self-virtualizing network interface on an embedded multicore platform. In Proceedings of the Workshop on the Interaction between Operating Systems and Computer Architecture, 2005.
 
37
38
 
39
40
 
41
D. Gupta, R. Gardner, and L. Cherkasovah. Xen\Mon: Qo\Smonitoring and performance profiling tool. Technical Report HPL-2005-187, HP Labs, 2005.
 
42

Collaborative Colleagues:
Chuliang Weng: colleagues
Zhigang Wang: colleagues
Minglu Li: colleagues
Xinda Lu: colleagues