Performance Impact of Advance Reservations from the Grid on Backfill Algorithms

Li, Bo; Zhao, Dongfeng

doi:10.1109/gcc.2007.96

Cited by 13 publications

(11 citation statements)

References 5 publications

(10 reference statements)

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“…In the next step, AR mechanism in both mentioned backfilling methods was incorporated. This is done based on [19], but differs from flexibility point of view.…”

Section: B Incorporation Of Ar Mechanism In Backfillingmentioning

confidence: 99%

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Flexible Advance Reservation Impact on Backfilling Scheduling Strategies

Moaddeli

Dastghaibyfard

Moosavi

2008

2008 Seventh International Conference on Grid and Cooperative Computing

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Advance Reservation mechanism was introduced in Grid environments to provide time Quality of Service requirements for time critical applications. Also there are applications that need resource coordination namely coallocation and workflow, which benefits from this capability.Contemporary trend in Grid computing is toward flexibility, because of its advantages in Advance Reservation such as increasing accept rate. This mechanism should be supported by local scheduler which is responsible for normal jobs. Using Backfilling methods with FCFS priority for scheduling normal jobs is the dominant approach. Therefore well investigation of performance impact of flexible Advance Reservation on backfilling scheduling is essential.In this paper incorporation of flexible Advance Reservation in major backfilling policies is investigated, regarding workload parameters impact on well known performance metrics. Here also the impact of increasing inaccuracy of user estimated job runtime is studied.Our experimental results indicate that aggressive backfilling algorithm is biased toward AR related performance metrics but conservative method has better job performance. Although more flexibility in advance reservation would improve AR performance but its impact on degrade of job performance metrics is noteworthy. Both parameter types' rates are less in conservative method. Moreover, usually increasing inaccuracy interestingly has opposing effect on backfilling methods.

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“…In the next step, AR mechanism in both mentioned backfilling methods was incorporated. This is done based on [19], but differs from flexibility point of view.…”

Section: B Incorporation Of Ar Mechanism In Backfillingmentioning

confidence: 99%

“…In [19] Li compared the effect of AR, in different backfilling scheduling policies, on the performance metrics by means of real parallel workload traces. There again, AR model used, unlike the preferred approach, is in a rigid style.…”

Section: Related Workmentioning

confidence: 99%

Flexible Advance Reservation Impact on Backfilling Scheduling Strategies

Moaddeli

Dastghaibyfard

Moosavi

2008

2008 Seventh International Conference on Grid and Cooperative Computing

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“…To this end, techniques such as backfilling [18] and advance reservations with flexible time constraints [11,14] are considered as a means to enhance utilization. In [23], SLAs are combined with flexible advance reservations, which are scheduled based on their flexibility.…”

Section: Related Workmentioning

confidence: 99%

Optimum allocation of distributed service workflows with probabilistic real-time guarantees

Konstanteli

Cucinotta

Varvarigou

2010

SOCA

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This paper addresses the problem of optimum allocation of distributed real-time workflows with probabilistic service guarantees over a set of physical resources. The discussion focuses on how such a problem may be mathematically formalized, in terms of both constraints and objective function to be optimized, which also accounts for possible business rules for regulating the deployment of the workflows. The presented formal problem constitutes a probabilistic admission control test that may be run by a provider in order to decide whether or not it is worth to admit new workflows into the system and to decide what the optimum allocation of the workflow to the available resources is. Various options are presented, which may be plugged into the formal problem description, depending on the specific needs of individual workflows. The presented problem has been implemented using GAMS and has been tested under various solvers. An illustrative numerical example and an analysis of the results of the implemented model under realistic settings are presented.

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“…In case of slack-based [34] and selective backfilling [31] the number of jobs with a reservation is related to their current wait time and slowdown respectively. Conservative backfilling [4,31,22] makes reservation for every queued job which cannot be executed at the given moment. It means that backfilling is performed only when it does not delay any previous job in the queue.…”

Section: Fairness Vs Performance In Scheduling Algorithmsmentioning

confidence: 99%

“…In order to deal with this situation we have proposed an optimization procedure designed to improve the performance of well known Conservative backfilling algorithm [4,31,22]. The choice of Conservative backfilling is straightforward as it allows predictability by establishing reservation for every waiting job.…”

Section: Introductionmentioning

confidence: 99%

Performance and Fairness for Users in Parallel Job Scheduling

Klusáček

Rudová

2013

Job Scheduling Strategies for Parallel Processing

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Abstract.In this work we analyze the performance of scheduling algorithms with respect to fairness. Existing works frequently consider fairness as a job related issue. In our work we analyze fairness with respect to different users of the system as this is a very important real-life problem. First, we discuss how fair are selected popular scheduling algorithms with respect to different users of the system. Next, we present an extension to the well known Conservative backfilling algorithm. Instead of "ad hoc" decisions, the schedule is now created subject to evaluation and optimization. Notably, the fairness is considered as an important metric, which accompanies standard performance related metrics such as slowdown or wait time. To achieve that, an inclusion of fairness as an optimization criterion is proposed. The new extension improves the performance and fairness of Conservative backfilling with respect to other classical techniques such as FCFS, EASY backfilling or aggressive backfilling without reservations.

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Performance Impact of Advance Reservations from the Grid on Backfill Algorithms

Cited by 13 publications

References 5 publications

Flexible Advance Reservation Impact on Backfilling Scheduling Strategies

Flexible Advance Reservation Impact on Backfilling Scheduling Strategies

Optimum allocation of distributed service workflows with probabilistic real-time guarantees

Performance and Fairness for Users in Parallel Job Scheduling

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