Implementation of Monitoring and Information Service Using Ganglia and NWS for Grid Resource Brokers

Yang, Chao‐Tung; Chen, Tsui-Ting; Chen, Sung-Yi

doi:10.1109/apscc.2007.74

Cited by 11 publications

(10 citation statements)

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“…In this section, we describe the system design and implementation of resource broker based on our previous works [43,44]. Figure 1 shows the system architecture of our Grid resource broker, which contains the components represented by rectangles: the Global Queue, Information Service, Information Center, Workflow Maker, Job Monitor, and Monitoring Service.…”

Section: System Design and Implementationmentioning

confidence: 99%

“…Two services, the Information Service and the Monitoring Service, were retained to achieve this. Figure 4 depicts the Information Service, Monitoring Service, and Resource Broker architectures of our previous version [44,47]. Unlike It employs the Ganglia and the NWS to collect resource information and current network bandwidth.…”

Section: Machine and Network Information Aggregatormentioning

confidence: 99%

“…Our previous link-bandwidth measurement scheme [44,47] measures a total of NMN(n) = n ×(n −1) network links per T seconds, producing a huge amount of measurement traffic and degrading system performance where n is the number of nodes in the Grid of concern. One of our previous works [11] proposed the domain-based network information model which is a static link-measure model.…”

Section: Dynamic Domain-based Network Information Modelmentioning

confidence: 99%

“…The main steps are (1) dump an RRD file and convert the file to XML format; (2) convert the XML file to JRobin RrdDB format, where RrdDB is a class of JRobin, and a constructor is also provided to create a new RRD from XML dump; and (3) render the graph of JRobin RrdDB by RrdGraphDef. The scripts of the three steps are listed in [44].…”

Section: Machine and Network Information Aggregatormentioning

confidence: 99%

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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: System Design and Implementationmentioning

confidence: 99%

Section: Machine and Network Information Aggregatormentioning

confidence: 99%

Section: Dynamic Domain-based Network Information Modelmentioning

confidence: 99%

Section: Machine and Network Information Aggregatormentioning

confidence: 99%

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

Yang

Leu

Chen

2010

Concurrency and Computation

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“…The Ganglia project grew out of the University of California, Berkeley's Millennium initiative [32]. Ganglia is a scalable distributed open-source system for monitoring node statuses (processor collections) in cluster-based wide-area systems.…”

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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Design and Implementation of a Multi-Grid Resource Broker for Grid Computing

Yang

2011

Data Driven E-Science

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Implementation of Monitoring and Information Service Using Ganglia and NWS for Grid Resource Brokers

Cited by 11 publications

References 10 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 Multi-Grid Resource Broker for Grid Computing

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