Impact of Laxity on Scheduling with Advance Reservations in Grids

Farooq, Umar; Majumdar, Shikharesh; Parsons, Eric W.

doi:10.1109/mascots.2005.33

Cited by 23 publications

(24 citation statements)

References 5 publications

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“…The existing studies on advance reservation with more relaxed start time, either assume that the start time and/or end time are static, i.e., the laxity is limited and use rescheduling at run-time, reallocating existing advance reservations at execution time and/or by changing the priority of the running service to ensure that the execution completes prior to its deadline [5] [6]. In many cases the algorithms behind these studies are mainly performance-driven and ignore resource sharing.…”

Section: Related Workmentioning

confidence: 99%

Real-Time Guarantees in Flexible Advance Reservations

Konstanteli

Kyriazis

Varvarigou

et al. 2009

2009 33rd Annual IEEE International Computer Software and Applications Conference

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Abstract-This paper deals with the problem of scheduling workflow applications with Quality of Service (QoS) constraints, comprising real-time and interactivity constraints, over a serviceoriented Grid network. A novel approach is proposed, in which high-level Advance Reservations, supporting flexible start and end time, are combined with low-level soft real-time scheduling, allowing for the concurrent deployment of multiple services on the same host while fulfilling their QoS requirements. By undertaking a stochastic approach, in which a-priori knowledge is leveraged about the probability of activation of the application workflows within the reserved time-frame, the proposed methodology allows for the achievement of various trade-offs between the need for respecting QoS constraints (user perspective) and the need for having good resource saturation levels (service provider perspective).

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Section: Related Workmentioning

confidence: 99%

Real-Time Guarantees in Flexible Advance Reservations

Konstanteli

Kyriazis

Varvarigou

et al. 2009

2009 33rd Annual IEEE International Computer Software and Applications Conference

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“…In [5], [6] authors investigated the negative impact advance reservations have on system and user performance. In [31], [43], [44] authors show how laxity and fuzziness in the reservation requests may be exploited to address some of the drawbacks of advance reservations. Two of the most recent major works on advance reservations in Grids are [32] and [21].…”

Section: Introductionmentioning

confidence: 99%

Efficient resource management using advance reservations for heterogeneous Grids

Castillo

Rouskas

Harfoush

2008

2008 IEEE International Symposium on Parallel and Distributed Processing

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Abstract-Support for advance reservations of resources plays a key role in Grid resource management as it enables the system to meet user expectations with respect to time requirements and temporal dependence of applications, increases predictability of the system and enables coallocation of resources. Despite these attractive features, adoption of advance reservations is limited mainly due to the fact that related algorithms are typically complex and fail to scale to large and loaded systems. In this work we consider two aspects of advance reservations. First, we investigate the impact of heterogeneity on Grid resource management when advance reservations are supported. Second, we employ techniques from computational geometry to develop an efficient heterogeneity-aware scheduling algorithm. Our main finding is that Grids may benefit from high levels of resource heterogeneity, independently of the total system capacity. Our results show that our algorithm performs well across several user and system performance and overcome the lack of scalability and adaptability of existing mechanisms.

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“…It has been shown that scheduling jobs with given start times, execution times and deadlines is an NP-Hard problem even if we consider a non-shared resource model [12]. In previous papers, we have presented scalable algorithms for scheduling ARs for both nonshared [6,9] and shared [10] resource models.…”

Section: Background and Related Workmentioning

confidence: 99%

“…The goal of the resource broker is to efficiently map jobs to different resources and the goal of the scheduler is to order jobs mapped to a particular resource to achieve specified time requirements. In earlier papers [6,9,10], we have shown how laxity in the reservation window can help improve resource utilizations of AR based scenarios by leaving the final scheduling decision with the scheduler. Laxity of an AR on a certain resource is the difference between its deadline and the time at which it would finish executing on that resource if it starts executing at its earliest start time.…”

Section: Introductionmentioning

confidence: 99%

“…Laxity of an AR on a certain resource is the difference between its deadline and the time at which it would finish executing on that resource if it starts executing at its earliest start time. Earlier, we have presented scalable algorithms for scheduling ARs mapped to a given resource [6,9,10]. In this paper, we focus on the mapping component as our results show that the algorithm for mapping ARs to resources, herein called matchmaking, can significantly affect performance.…”

Section: Introductionmentioning

confidence: 99%

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