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Fairness and efficiency in web server protocols
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Source Joint International Conference on Measurement and Modeling of Computer Systems archive
Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems table of contents
San Diego, CA, USA
SESSION: Scheduling table of contents
Pages: 229 - 237  
Year of Publication: 2003
ISBN:1-58113-664-1
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Authors
Eric J. Friedman  Cornell University, Ithaca, NY
Shane G. Henderson  Cornell University, Ithaca, NY
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 5,   Downloads (12 Months): 40,   Citation Count: 10
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ABSTRACT

We consider the problem of designing a preemptive protocol that is both fair and efficient when one is only concerned with the sojourn time of the job and not intermediate results. Our Fair Sojourn Protocol (FSP) is both efficient, in a strong sense (similar to the shortest remaining processing time protocol: SRPT), and fair, in the sense of guaranteeing that it weakly outperforms processor sharing (PS) for every job on any sample path.Our primary motivation is web serving in which the standard protocol is PS, while recent work proposes using SRPT or variants. Our work suggests both a framework in which to evaluate proposed protocols and an attractive new protocol, FSP.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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A. Demers, S. Keshav, and S. Shenker. Analysis and simulation of a fair queueing algorithm. Journal of Internetworking, 1(1):3--26, Jan. 1990.
 
6
M. Harchol-Balter, N. Bansal, B. Schroeder, and M. Agrawal. Size-based scheduling to improve web performance. Mimeo, CMU, 2001.
 
7
E. Modiano. Scheduling algorithms for message transmission over a satellite broadcast system. In Proceedings of IEEE MILCOM'97, pages 628---634, 1997.
 
8
 
9
H. Moulin. Axioms of Cooperative Decision Making. Cambridge University Press, New York, 1991.
 
10
H. Moulin. Axiomatic cost and surplus-sharing. In Arrow, Sen, and Suzumura, editors, Handbook of Social Choice and Welfare. North-Holland, New York, 2002.
 
11
 
12
L. Schrage. A proof of the optimality of the shortest remaining processing time discipline. Operations Research, 16:687---690, 1968.
 
13
D. Smith. A new proof of the optimality of the shortest remaining processing time discipline. Operations Research, 26:197---199, 1976.
 
14
W. Stallings. Operating Systems. Prentice Hall, 2nd edition, 1995.
 
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H. P. Young. Cost Allocation: Methods, Principles and Applications. Elsevier Science, New York, 1985.

CITED BY  10

Collaborative Colleagues:
Eric J. Friedman: colleagues
Shane G. Henderson: colleagues