On unreliable computing systems when heavy-tails appear as a result of the recovery procedure

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On unreliable computing systems when heavy-tails appear as a result of the recovery procedure

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ACM SIGMETRICS Performance Evaluation Review archive
Volume 33 , Issue 2 (September 2005) table of contents
Special issue on the workshop on MAthematical performance Modeling And Analysis (MAMA 2005)

Pages: 15 - 17

Year of Publication: 2005

ISSN:0163-5999

Authors

Pierre M. Fiorini	University of Southern Maine, Portland, ME
Robert Sheahan	University of Connecticut, Storrs, CT
Lester Lipsky	University of Connecticut, Storrs, CT

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 1, Downloads (12 Months): 7, Citation Count: 3

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ABSTRACT

For some computing systems, failure is rare enough that it can be ignored. In other systems, failure is so common that how to handle it can have a significant impact on the performance of the system. There are many different recovery schemes for tasks, however, they can be classified into three broad categories: 1) Resume: when a task fails, it knows exactly where it stops and can continue at that point when allowed to resume (i.e., preemptive resume - prs); 2) Replace: when a task fails, then later when the processor continues, it begins with a brand new task (i.e., preemptive repeat different prd); and, 3) Restart: when a task fails it loses all work done to that point and must start anew upon continuing later (i.e., preemptive repeat identical - pri).In this paper, assuming a computing system is unreliable, we discuss how heavy-tail (hereafter referred to as power-tail - PT) distributions can appear in a job's task stream given the Restart recovery procedure. This is an important consideration since it is known that power-tails can lead to unstable systems [4], We then demonstrate how to obtain performance and dependablity measures for a class of computing systems comprised of P unreliable processors and a finite number of tasks N given the above recovery procedures.

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.

	1	A. Bobbio and K. Trivedi, "Computation of the Distribution of the Completion Time When the Work Requirement is a PH Random Variable", Communications in Statistics - Stochastic Models, 1990.
	2	Michael Greiner , Manfred Jobmann , Lester Lipsky, The Importance of Power-Tail Distributions for Modeling Queueing Systems, Operations Research, v.47 n.2, p.313-326, February 1999
	3	V. Kulkarni, V. Nicola, and K. Trivedi, "The Completion Time of a Job on a Multmode System," Advances in Applied Probability, 19:932--954, 1987.
	4	L. Lipsky, Queueing Theory: A Linear Algebraic Approach, MacMillan and Company, New York, 1992.

CITED BY 3

	Craig Bossie , Pierre M. Fiorini, On checkpointing and heavy-tails in unreliable computing environments, ACM SIGMETRICS Performance Evaluation Review, v.34 n.2, September 2006
	Robert Sheahan , Lester Lipsky , Pierre M. Fiorini , Søren Asmussen, On the completion time distribution for tasks that must restart from the beginning if a failure occurs, ACM SIGMETRICS Performance Evaluation Review, v.34 n.3, December 2006
	Predrag R. Jelenković , Jian Tan, Dynamic packet fragmentation for wireless channels with failures, Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing, May 26-30, 2008, Hong Kong, Hong Kong, China