An Efficient Network Information Model Using NWS for Grid Computing Environments

Yang, Chao‐Tung; Shih, Po-Chi; Chen, Sung-Yi; Shih, Wen-Chung

doi:10.1007/11590354_40

Cited by 16 publications

(12 citation statements)

References 6 publications

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“…In this study, Getter and Setter provides a new function that responds to information-collection and data-access requests submitted by users. (4) Predictor: It periodically retrieves raw data from the Message Center (modular design allows various types of raw data for adaptation to our previous prediction models [10,19]), and accepts requests issued by the Agent (described below) to predict and obtain required data. This component was applicable to any applications that need to predict future values.…”

Section: Machine and Network Information Aggregatormentioning

confidence: 99%

Resource brokering using a multi‐site resource allocation strategy for computational grids

Yang

Leu

Chen

2010

Concurrency and Computation

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SUMMARYGrid computing employs heterogeneous resources which may be installed on different platforms, hardware/software, computer architectures, and perhaps using different computer languages to solve large-scale computational problems. As many more Grids are being developed worldwide, the number of multi-institutional collaborations is growing rapidly. However, to realize Grid computing's full potential, it is expected that Grid participants must be able to share one another's resources. This paper presents a resource broker that employs the multi-site resource allocation (MSRA) strategy and the dynamic domain-based network information model that we propose to allocate Grid resources to submitted jobs, where the Grid resources may be dispersed at different sites, and owned and governed by different organizations or institutes. The jobs and resources may also belong to different clusters/sites. Resource statuses collected by the Ganglia, and network bandwidths gathered by the Network Weather Service, are both considered in the proposed scheduling approach. A dynamic domain-based model for network information measurement is also proposed to choose the most appropriate resources that meet the jobs' execution requirements. Experimental results show that MSRA outperformed the other tested strategies.

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Section: Machine and Network Information Aggregatormentioning

confidence: 99%

Resource brokering using a multi‐site resource allocation strategy for computational grids

Yang

Leu

Chen

2010

Concurrency and Computation

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“…The Network Weather Service (NWS) is a distributed system that employs a set of distributed performance sensors to detect network statuses by periodically monitoring Grid resources [16,17,30] and gathering system information of concern, including end-to-end TCP/IP performance (bandwidth and latency), available CPU percentage, and available nonpaged memory. The NWS then forecasts what the conditions will be for given time periods with numerical methods/models.…”

Section: Middleware For Grid Computingmentioning

confidence: 99%

Network Bandwidth-aware job scheduling with dynamic information model for Grid resource brokers

2008

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A resource broker with a user-friendly interface for job submission developed on a platform constructed using the Globus toolkit is proposed. The broker employs a domain-based network information model and dynamic version to measure network statuses, and also monitors and collects resource statuses and networkrelated information as the basis of its brokerage. A network bandwidth-aware job scheduling algorithm for brokering suitable Grid resources to communicationintensive jobs based on improving and preserving the advantages of our previously developed network information model is also proposed. Using timely information, the resource broker effectively matches Grid resources and user requests, thus improving job execution efficiency.

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“…Then we consider inaccuracies in real-world network values in generating approximation values for future use. The details of the network information model will be discussed in [22,23].…”

Section: Phase 2-information Gatheringmentioning

confidence: 99%

“…We perform this step by two actions. First, transfer the machine list needed for MPI [17,[19][20][21][22] to the first machine in our machine list via GridFTP, because the first is the best choice based on the application model. The second action is to transfer the application to every available resource.…”

Section: Phase 5-job Executionmentioning

confidence: 99%

“…Because grid resources are dynamically changeable, real-time information allows for successful dynamical scheduling. We implement this step by using Ganglia [24] and NWS [22,23]. The Network Weather Service (NWS) is a distributed system that detects network status by periodically monitoring and dynamically forecasting over a given time interval [23].…”

Section: Phase 2-information Gatheringmentioning

confidence: 99%

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Design and implementation of a workflow-based resource broker with information system on computational grids

2008

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The grid is a promising infrastructure that can allow scientists and engineers to access resources among geographically distributed environments. Grid computing is a new technology which focuses on aggregating resources (e.g., processor cycles, disk storage, and contents) from a large-scale computing platform. Making grid computing a reality requires a resource broker to manage and monitor available resources. This paper presents a workflow-based resource broker whose main functions are matching available resources with user requests and considering network information statuses during matchmaking in computational grids. The resource broker provides a graphic user interface for accessing available and the appropriate resources via user credentials. This broker uses the Ganglia and NWS tools to monitor resource status and network-related information, respectively. Then we propose a history-based execution time estimation model to predict the execution time of parallel applications, according to previous execution results. The experimental results show that our model can accurately predict the execution time of embarrassingly parallel applications. We also report on using the Globus Toolkit to construct a grid platform called the TIGER project that integrates resources distributed across five universities in Taichung city, Taiwan, where the resource broker was developed.

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An Efficient Network Information Model Using NWS for Grid Computing Environments

Cited by 16 publications

References 6 publications

Resource brokering using a multi‐site resource allocation strategy for computational grids

Resource brokering using a multi‐site resource allocation strategy for computational grids

Network Bandwidth-aware job scheduling with dynamic information model for Grid resource brokers

Design and implementation of a workflow-based resource broker with information system on computational grids

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