Meteorology Grid Computing aims to provide scientist with seamless, reliable, secure and inexpensive access to meteorological resources. In this paper, we presented a semantic-based meteorology grid service registry, ...
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Memory-intensive applications often suffer from the poor performance of disk swapping when memory is inadequate. Remote memory sharing schemes, which provide a remote memory that is faster than the local hard disk, ar...
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Meteorology Grid Computing aims to provide scientist with seamless, reliable, secure and inexpensive access to meteorological resources. In this paper, we presented a semantic-based meteorology grid service registry, ...
详细信息
Meteorology is a complex, interdisciplinary area. Meteorology Grid Computing tries to offer a flexible, secure, coordinated resource sharing and problem-resolving environment by making good use of semantic grid ideas....
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Meteorology Grid Computing aims to provide scientist with seamless, reliable, secure and inexpensive access to meteorological resources. In this paper, we presented a semantic-based meteorology grid service registry, ...
Meteorology Grid Computing aims to provide scientist with seamless, reliable, secure and inexpensive access to meteorological resources. In this paper, we presented a semantic-based meteorology grid service registry, discovery and composition framework by combining grid technologies and the advantages of semantic web techniques. The main objective of the framework is to support automating the discovery, selection, and workflow composition of semantically described heterogeneous meteorological grid services, which offers the possibility of facilitating geographically distributed meteorological scientists to resolve complex scientific problems cooperately. With this framework, the key technologies such as semantic registry, semantic matchmaking, QoS ranking and composition model, will be discussed.
Memory-intensive applications often suffer from the poor performance of disk swapping when memory is inadequate. Remote memory sharing schemes, which provide a remote memory that is faster than the local hard disk, ar...
详细信息
ISBN:
(纸本)9781424400546
Memory-intensive applications often suffer from the poor performance of disk swapping when memory is inadequate. Remote memory sharing schemes, which provide a remote memory that is faster than the local hard disk, are able to improve the performance of such applications. Due to the limitation of being applicable within single clusters only, however, most of the previous remote memory mechanisms, such as the network memory scheme, fail to be extendable into a large scale, distributed, heterogeneous, and dynamic environment. In this work, we propose a service-oriented grid memory sharing scheme, distributed paging RAM grid (DPRG). We study the properties and criteria of large scale memory sharing, and then design major operations and optimizations to fit the usage of grid systems. We collect trace from our grid environment, and evaluate DPRG through comprehensive trace-driven simulations. Results show that DPRG significantly outperforms existing remote memory sharing schemes and supports grid computing applications effectively
Meteorology grid computing aims to provide scientist with seamless, reliable, secure and inexpensive access to meteorological resources. However, the vision of achieving these goals has been encountered with many chal...
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Meteorology grid computing aims to provide scientist with seamless, reliable, secure and inexpensive access to meteorological resources. However, the vision of achieving these goals has been encountered with many challenges such as the degree of easy-to-use and the capability of seamless automation. Fortunately, the emerging semantic Web service and semantic grid technologies bring some significant solutions for the above challenges. Semantic meteorology grid architecture (SMGA) is being developed by us to support automated meteorology grid service discovery, selection, and composition. In this paper, we present a model for semantic annotation and publication of meteorology grid services by combining the expressive power of the present ontology language and the advantages of semantic Web techniques. The presented model is an initial work to support automating the discovery, selection, and workflow composition of semantically described heterogeneous meteorological services, which offers the possibility of facilitating geographically distributed meteorological scientists to resolve complex scientific problems cooperatively
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