Reputation-Based Scheduling on Unreliable Distributed Infrastructures

Sonnek, Jason; Nathan, M. I.; Chandra, Abhishek; Weissman, Jon

doi:10.1109/icdcs.2006.70

Cited by 36 publications

(21 citation statements)

References 17 publications

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“…Авторы [34,37] определяют надежность вычислительного узла, как его вероятность вернуть результат, не нарушив срока обработ-ки. Уровень надежности вычисляется на основе числа полученных правильных ответов.…”

Section: исследовательские статьиunclassified

A survey of task scheduling in Desktop Grid

Chernov¹,

Ivashko²,

Nikitina³

2017

PSTA

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Section: исследовательские статьиunclassified

A survey of task scheduling in Desktop Grid

Chernov¹,

Ivashko²,

Nikitina³

2017

PSTA

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“…Here, we use redundancy for achieving robust scheduling guarantees. Reputation-based scheduling: There are a number of papers that have proposed the use of reputation to store the trust and reliability values of nodes for use in scheduling [38,33,9]. However, many of these systems do not consider task deadlines which creates a second dimension in the reputation computation, as shown by our use of node timeliness distribution, rather than each node having a fixed reputation across all tasks.…”

Section: Fairness In Schedulingmentioning

confidence: 99%

Exploring the throughput-fairness tradeoff of deadline scheduling in heterogeneous computing environments

Sundaram

Chandra

Weissman

2008

SIGMETRICS Perform. Eval. Rev.

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The scalability and computing power of large-scale computational platforms that harness processing cycles from distributed nodes has made them attractive for hosting compute-intensive time-critical applications. Many of these applications are composed of computational tasks that require specific deadlines to be met for successful completion. In scheduling such tasks, replication becomes necessary due to the heterogeneity and dynamism inherent in these computational platforms. In this paper, we show that combining redundant scheduling with deadline-based scheduling in these systems leads to a fundamental tradeoff between throughput and fairness. We propose a new scheduling algorithm called Limited Resource Earliest Deadline (LRED) that couples redundant scheduling with deadline-driven scheduling in a flexible way by using a simple tunable parameter to exploit this tradeoff. Our evaluation of LRED using trace-driven and synthetic simulations shows that LRED provides a powerful mechanism to achieve desired throughput or fairness under high loads and low timeliness environments, where these tradeoffs are most critical.

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“…The group that has the maximum reputation value becomes the honest group [20]. We refer to these traditional reputation methods [20], [23] as the existing method for simplicity. The following example shows how the existing reputation-based method is carried out: Example 1) Consider workers w i for 1 ≤ i ≤ 7, and tasks T j for 1 ≤ j ≤ 4.…”

Section: Existing Reputation-based Methodsmentioning

confidence: 99%

Reputation-Based Collusion Detection with Majority of Colluders

Hur¹,

Guo

Park

et al. 2016

IEICE Trans. Inf. & Syst.

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SUMMARYThe reputation-based majority-voting approach is a promising solution for detecting malicious workers in a cloud system. However, this approach has a drawback in that it can detect malicious workers only when the number of colluders make up no more than half of all workers. In this paper, we simulate the behavior of a reputation-based method and mathematically analyze its accuracy. Through the analysis, we observe that, regardless of the number of colluders and their collusion probability, if the reputation value of a group is significantly different from those of other groups, it is a completely honest group. Based on the analysis result, we propose a new method for distinguishing honest workers from colluders even when the colluders make up the majority group. The proposed method constructs groups based on their reputations. A group with the significantly highest or lowest reputation value is considered a completely honest group. Otherwise, honest workers are mixed together with colluders in a group. The proposed method accurately identifies honest workers even in a mixed group by comparing each voting result one by one. The results of a security analysis and an experiment show that our method can identify honest workers much more accurately than a traditional reputation-based approach with little additional computational overhead.

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Reputation-Based Scheduling on Unreliable Distributed Infrastructures

Abstract: Abstract

Cited by 36 publications

References 17 publications

A survey of task scheduling in Desktop Grid

A survey of task scheduling in Desktop Grid

Exploring the throughput-fairness tradeoff of deadline scheduling in heterogeneous computing environments

Reputation-Based Collusion Detection with Majority of Colluders

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