Fault-tolerant resource allocation for query processing in grid environments

Çokuslu, Deniz; Hameurlain, Abdelkader; Erciyes, K.

doi:10.1504/ijwgs.2015.068895

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Delivering Utility Services Through Grid1

Introduction1

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Cited by 4 publications

(2 citation statements)

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“…The task of providing a powerful and robust platform that can make the resources accessible to the users easily without any deep technical knowledge is a complex job. On the other hand, the services such as job scheduling, load balancing, resource discovery and allocation pose intricate management risks [63,64]. Other critical success factors include ever changing market demands and design of efficient resource scheduling algorithms.…”

Section: Delivering Utility Services Through Gridmentioning

confidence: 99%

Delivering IT as A Utility- A Systematic Review

Chana¹,

Kaur²

2013

IJFCST

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Section: Delivering Utility Services Through Gridmentioning

confidence: 99%

Delivering IT as A Utility- A Systematic Review

Chana¹,

Kaur²

2013

IJFCST

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“…Since most multi-clusters, grid and cloud computing platforms have been built on top of the existing local resource management systems, a hierarchy of schedulers has been naturally established [3,4,5]. A typical scheduling prototype in grid platforms is shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

Scalable Hierarchical Scheduling for Malleable Parallel Jobs on Multiprocessor-based Systems

Cao¹,

Sun²,

Qian³

et al. 2014

Preprint

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The proliferation of multi-core and multiprocessor-based computer systems has led to explosive development of parallel applications and hence the need for efficient schedulers. In this paper, we study hierarchical scheduling for malleable parallel jobs on multiprocessor-based systems, which appears in many distributed and multilayered computing environments. We propose a hierarchical scheduling algorithm, named AC-DS, that consists of a feedback-driven adaptive scheduler, a desire aggregation scheme and an efficient resource allocation policy. From theoretical perspective, we show that AC-DS has scalable performance regardless of the number of hierarchical levels. In particular, we prove that AC-DS achieves O(1)-competitiveness with respect to the overall completion time of the jobs, or the makespan. A detailed malleable job model is developed to experimentally evaluate the effectiveness of the proposed scheduling algorithm. The results verify the scalability of AC-DS and demonstrate that AC-DS outperforms other strategies for a wide range of parallel workloads.

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