Architectural Models for Resource Management in the Grid

Buyya, Rajkumar; Chapin, Steve J.; DiNucci, David C.

doi:10.1007/3-540-44444-0_3

Cited by 84 publications

(50 citation statements)

References 7 publications

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“…Collecting and assessing resources information in heterogeneous environments is a complex task because resources are geographically dispersed, owned by different organizations, and restricted by different management policies and access rights [14]. Each resource discovery service makes use of a resource status database to carry out clients requests.…”

Section: Resource Discoverymentioning

confidence: 99%

Survey on Grid Resource Allocation Mechanisms

et al. 2014

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Grid is a distributed high performance computing paradigm that offers various types of resources (like computing, storage, communication) to resource-intensive user tasks. These tasks are scheduled to allocate available Grid resources efficiently to achieve high system throughput and to satisfy A. Y. Zomaya University of Sydney, Sydney, Australia user requirements. The task scheduling problem has become more complex with the ever increasing size of Grid systems. Even though selecting an efficient resource allocation strategy for a particular task helps in obtaining a desired level of service, researchers still face difficulties in choosing a suitable technique from a plethora of existing methods in literature. In this paper, we explore and discuss existing resource allocation mechanisms for resource allocation problems employed in Grid systems. The work comprehensively surveys Gird resource allocation mechanisms for different architectures (centralized, distributed, static or dynamic). The paper also compares these resource allocation mechanisms based on their common features such as time complexity, searching mechanism, allocation strategy, optimality, operational environment and objective function they adopt for solving computing-and data-intensive applications. The comprehensive analysis of cutting-edge research in the Grid domain presented in this work provides readers with an understanding of essential concepts of resource allocation mechanisms in Grid systems and helps them identify important and outstanding issues for further investigation. It also helps readers to choose the most appropriate mechanism for a given system/application.

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Section: Resource Discoverymentioning

confidence: 99%

Survey on Grid Resource Allocation Mechanisms

et al. 2014

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“…Since a data object is a group of files that tend to be accessed together and the accesses to different data objects are assumed to be independent, each job only requests for one data object. As typical for many data grids [5], we assume that requests are submitted to a global computational scheduler, which decides and distributes requests to their proper execution sites. Let λ denote the job request rate for the data grid and λ i be the request rate for site i.…”

Section: System Modelmentioning

confidence: 99%

“…First, it generates a list (L h ) that includes the most popular data objects whose replications are expected to cause the workload of site h, to reduce below the target (lines [4][5][6][7][8][9][10][11][12][13][14][15][16]. That is, j∈L h Δλ hj ≥ Δλ h .…”

Section: Data Replication Algorithmmentioning

confidence: 99%

Automatic data placement and replication in grids

Ding

Lü

2009

2009 International Conference on High Performance Computing (HiPC)

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“…Scheduling problem is a NP-Complete problem [10], which means that ordinary algorithms with non-optimization are impractical. Current job scheduling algorithms are mainly based on User-Directed Assignment (UDA), Minimum Completion Time (MCT), Minimum Execution Time (MET), Min-Min [7], MaxMin [13], genetic algorithm (GA) [15], ant algorithm (AA) [8], multi-Agent, computational economy model [4,9,20], and so on. All of these algorithms are dedicated to improve the Qos of grid computing.…”

Section: Related Workmentioning

confidence: 99%

Research on Fine-grained Job scheduling in Grid Computing

Liao

Liu²

2009

IJIEEB

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Abstract-Grid computing is the technology used in building Internet-wide computing environment and integrating distributed and heterogeneous resources. However, in Grid environment, job scheduling is confronted with a great challenge. This paper focuses on lightweight jobs scheduling in Grid Computing. An Adaptive Fine-grained Job Scheduling (AFJS) algorithm is proposed. Compared with other fine-grained job scheduling algorithms based on grouping, AFJS can outperform them according to the experimental results. And some other related problems are also illustrated.

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Architectural Models for Resource Management in the Grid

Cited by 84 publications

References 7 publications

Survey on Grid Resource Allocation Mechanisms

Survey on Grid Resource Allocation Mechanisms

Automatic data placement and replication in grids

Research on Fine-grained Job scheduling in Grid Computing

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