SERVOGrid complexity computational environments (CCE) integrated performance analysis

Aydın, Galip; Aktaş, Mehmet S.; Fox, Geoffrey; Gadgil, Harshawardhan; Pierce, Marlon; Sayar, Ahmet

doi:10.1109/grid.2005.1542750

Cited by 40 publications

(20 citation statements)

References 9 publications

(7 reference statements)

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“…The main goal of this experiment is to investigate how the system performs in a real application case scenario such as Patten Informatics workflow-style GIS application [1]. In this motivating scenario: GPS, Fault, and Seismic data bases, wrapped by OpenGIS web services, filtering and geo-processing services are distributed across various institutions.…”

Section: Experiments 3 -Experiments Designed Based On Application Use Cmentioning

confidence: 99%

“…The network bandwidth between these machines was 900 Mbits/sec. 1 We tested the performance of the FTHPIS with a client program called WSContextClient (a program for sending queries to WS-Context Service) and a provider program WSContextProvider (a program for publishing context to FTHPIS). Both WSContextClient and WSContextProvider are multithreaded programs.…”

Section: Environmentmentioning

confidence: 99%

“…E-Science Semantic Grids can often be thought of as dynamic collection of semantic subgrids where each subgrid is a collection of modest number of services that assembled for specific tasks such as forecasting earthquakes [1] or managing an audio/video collaboration session [3]. We term an actively interacting (collaborating) set of managed and modest number of services as a Gaggle where services are put together for particular functionality.…”

Section: Introductionmentioning

confidence: 99%

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Fault tolerant high performance Information Services for dynamic collections of Grid and Web services

Aktaş

Fox

Pierce

2007

Future Generation Computer Systems

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Abstract. E-Science Semantic Grids can often be thought of as dynamic collection of semantic subgrids where each subgrid is a collection of modest number of services that assembled for specific tasks. We define a Gaggle as a modest number of managed and actively interacting Grid/Web Services, where services are put together for particular functionality. The information management requirements in Gaggles include both the management of large amounts of relatively static services and associated semantic information as well as the management of multiple dynamic regions (sessions or subgrids) where the semantic information is changing frequently. We design a hybrid, fault tolerant, and high performance Information Service supporting both the scalability of large amounts of relatively slowly varying data and a high performance rapidly updated Information Service for dynamic regions. We use the two Web Service standards: Universal Description, Discovery, and Integration (UDDI) and Web Services Context (WS-Context). We evaluate our approach by applying various tests to investigate the performance and sustainability of the centralized version of our implementation that is applied to sensor and collaboration grids. The experimental study on system responsiveness of the proposed approach shows promising results. This study indicates that communication among services can be achieved with efficient centralized metadata strategies, with metadata coming from more than two services. In contrast point-to-point methodologies provide service conversation with metadata only from the two services that exchange information. In addition, our performance indicates that efficient mediator services also allow us to perform collective operations such as queries on subsets of all available metadata in service conversation.

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Section: Experiments 3 -Experiments Designed Based On Application Use Cmentioning

confidence: 99%

Section: Environmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fault tolerant high performance Information Services for dynamic collections of Grid and Web services

Aktaş

Fox

Pierce

2007

Future Generation Computer Systems

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“…We applied the introduced system into different application domains such as geographical information system and sensor grids [4,[23][24][25], management of real-time streams in collaboration grids [26,27]. We intend to investigate how good the system architecture is by applying it into wider range of application domains.…”

Section: Conclusion and Future Research Directionsmentioning

confidence: 99%

High‐performance hybrid information service architecture

Aktaş

Pierce

2010

Concurrency and Computation

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Abstract. We introduce a distributed high performance hybrid Information Service Architecture, which forms a metadata replica hosting system to manage both highlydynamic, small-scale and relatively-large, static metadata associated to Grid/Web Services. We present an empirical evaluation of the proposed architecture and investigate its practical usefulness. The results demonstrate that the proposed system achieves highperformance and fault-tolerance with negligible processing overheads. The results also indicate that efficient decentralized Information Service Architectures can be built by utilizing publish-subscribe based messaging schemes.

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“…E-Science Semantic Grids can often be thought of as dynamic collection of semantic subgrids where each subgrid is a collection of modest number of services that assembled for specific tasks such as forecasting earthquakes [1]. We term an actively interacting (collaborating) set of managed services as a Gaggle where services are put together for particular functionality.…”

Section: Introductionmentioning

confidence: 99%