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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Rough set theory has been widely and successfully used in data mining, especially in classification field. But most existing rough set based classification approaches require computing optimal attribute reduction, whi...
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In this article we describe a method for selecting informative genes from microarray data. The method is based on clustering, namely, it first find similar genes, group them and then select informative genes from thes...
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There are many researches use peer-to-peer model to organize the grid information service (GIS) and have been testified which be able to improve scalability and reliability of grid environment. However, data grid info...
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There are many researches use peer-to-peer model to organize the grid information service (GIS) and have been testified which be able to improve scalability and reliability of grid environment. However, data grid information service (DGIS) has its special requirements and all approaches of P2P model used in GIS cannot be applied to DGIS. In this paper, we propose a new approach for DGIS that imposes a deterministic P2P shape based on hypercube topology, which allows for very efficient query broadcasting. Furthermore, we proposed a transposition algorithm to optimize the overlay network's topology according to the access statistics between peers, making the peers always access each other become neighbor by transposing peer's place. The simulation shows that the transposition algorithm could significant improve searches efficiency
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.
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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DNA sequence assembly is a fundamental part of biological computing. However, most of the large-scale sequence assemblies require intensive computing power and huge storage. To speed up the assembly process, we here p...
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DNA sequence assembly is a fundamental part of biological computing. However, most of the large-scale sequence assemblies require intensive computing power and huge storage. To speed up the assembly process, we here propose a method for large-scale DNA sequence assembly by using computing grid. The central idea of our method is to first cluster the input of fragment set into many non-intersected subsets using k-mers and then to distribute them to all nodes of the grid-computing system. Our method has accuracy of more than 92% on the test data sets under the simulated grid-computing system but costing shorter time and lower storage. Our method can efficiently process large-scale DNA sequence assembly by taking advantage of huge storage and computing capacity of computing gird
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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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
In this article we describe a method for selecting informative genes from microarray data. The method is based on clustering, namely, it first find similar genes, group them and then select informative genes from thes...
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In this article we describe a method for selecting informative genes from microarray data. The method is based on clustering, namely, it first find similar genes, group them and then select informative genes from these groups to avoid redundancy. A new gene similarity measure based on grey relational analysis (GRA), called grey relational grade (GRG), is used in clustering. Experiments on three public data sets demonstrate the effectiveness of our method
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