The Optimal Age-Dependent Checkpoint Strategy for a Stochastic System Subject to General Failure Mode

Kaio, Naoto; Osaki, Shunji

doi:10.1006/jmaa.2000.6939

Cited by 7 publications

(5 citation statements)

References 16 publications

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“…Preempting a job between checkpoints may be disallowed, or it may be undesirable due to the risk of losing progress. Most queueing-theoretic prior work on preemption checkpoints studies the problem of placing checkpoints to minimize lost progress [8,33,99].…”

Section: Preemption Checkpointsmentioning

confidence: 99%

A New Toolbox for Scheduling Theory

Scully

2022

SIGMETRICS Perform. Eval. Rev.

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Queueing delays are ubiquitous in many domains, including computer systems, service systems, communication networks, supply chains, and transportation. Queueing and scheduling theory provide a rigorous basis for understanding how to reduce delays with scheduling, including evaluating policy performance and guiding policy design. Unfortunately, stateof- the-art theory fails to address many practical concerns. For example, scheduling theory seldom treats nontrivial preemption limitations, and there is very little theory for scheduling in multiserver queues. My thesis presents two new, broadly applicable tools that greatly expand the reach of scheduling theory, using each to solve multiple open problems. The first tool, called "SOAP", is a new unifying theory of scheduling in single-server queues, specifically the M/G/1 model. SOAP characterizes the delay distribution of a broad space of policies, most of which have never been analyzed before. Such policies include the Gittins index policy, which minimizes mean delay in low-information settings, and many policies with preemption limitations. The second tool, called "WINE", is a new queueing identity that complements Little's law. WINE enables a new method of analyzing complex queueing systems by relating them to simpler systems. This results in the first delay bounds for Shortest Remaining Processing Time (SRPT) and the Gittins policy in multiserver queues, specifically the M/G/k model. This abstract gives a brief overview of my thesis, describing what the SOAP and WINE tools do, the key ideas underlying them, and the open problems they help solve.

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Section: Preemption Checkpointsmentioning

confidence: 99%

A New Toolbox for Scheduling Theory

Scully

2022

SIGMETRICS Perform. Eval. Rev.

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“…We focus on the size-oblivious setting with the high-variance job size distributions from Table 4.1. 9 For these job size distributions, FB is a near-optimal Gittins substitute, so we schedule using the version of FB with checkpoints shown in Fig. 5.1.…”

Section: Optimizing the Gap Between Checkpointsmentioning

confidence: 99%

“…Checkpointing has been well studied in queueing systems from the perspective of using checkpoints to minimize work lost in the event of system crashes [5,9,23]. However, this line of work assumes FCFS scheduling.…”

Section: Prior Work On Preemption Checkpoints (Section 5)mentioning

confidence: 99%

How to Schedule Near-Optimally under Real-World Constraints

Scully¹

2021

Preprint

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Scheduling is a critical part of practical computer systems, and scheduling has also been extensively studied from a theoretical perspective. Unfortunately, there is a gap between theory and practice, as the optimal scheduling policies presented by theory can be difficult or impossible to perfectly implement in practice. In this work, we use recent breakthroughs in queueing theory to begin to bridge this gap. We show how to translate theoretically optimal policies-which provably minimize mean response time (a.k.a. latency)-into near-optimal policies that are easily implemented in practical settings. Specifically, we handle the following real-world constraints:• We show how to schedule in systems where job sizes (a.k.a. running times) are unknown, or only partially known. We do so using simple policies that achieve performance very close to the much more complicated theoretically optimal policies. • We show how to schedule in systems that have only a limited number of priority levels available. We show how to adapt theoretically optimal policies to this constrained setting and determine how many levels we need for near-optimal performance. • We show how to schedule in systems where job preemption can only happen at specific checkpoints.Adding checkpoints allows for smarter scheduling, but each checkpoint incurs time overhead. We give a rule of thumb that near-optimally balances this tradeoff.

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“…First Young [4] obtains the optimal CP interval approximately for a computation restart after system failures. Baccelli [5], Chandy et al [6,7], Dohi et al [8][9][10], Gelenbe and Derochette [11], Gelenbe [12], Gelenbe and Hernandez [13], Goes and Sumita [14], Goes [15], Grassi et al [16], Kobayashi and Dohi [17], Kulkarni et al [18], Nicola and van Spanje [19], Sumita et al [20], among others, propose performance evaluation models for database recovery, and calculate the optimal CP intervals which maximize the system availability or minimize the mean overhead during the normal operation. L'Ecuyer and Malenfant [21] formulate a dynamic CP placement problem by a Markov decision process.…”

Section: Introductionmentioning

confidence: 99%

Aperiodic Checkpoint Placement Algorithms—Survey and Comparison

Hiroyama¹,

Okamura²

2013

JSEA

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In this article we summarize some aperiodic checkpoint placement algorithms for a software system over infinite and finite operation time horizons, and compare them in terms of computational accuracy. The underlying problem is formulated as the maximization of steady-state system availability and is to determine the optimal aperiodic checkpoint sequence. We present two exact computation algorithms in both forward and backward manners and two approximate ones; constant hazard approximation and fluid approximation, toward this end. In numerical examples with Weibull system failure time distribution, it is shown that the combined algorithm with the fluid approximation can calculate effectively the exact solutions on the optimal aperiodic checkpoint sequence. This is an extended version of the conference paper [1] presented at

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The Optimal Age-Dependent Checkpoint Strategy for a Stochastic System Subject to General Failure Mode

Cited by 7 publications

References 16 publications

A New Toolbox for Scheduling Theory

A New Toolbox for Scheduling Theory

How to Schedule Near-Optimally under Real-World Constraints

Aperiodic Checkpoint Placement Algorithms—Survey and Comparison

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