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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Data replication introduces well-known consistency issues. This paper puts forward the question about data dependence in data consistency, which embodies pseudo-conflict updates and update dependency. According to tha...
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Data replication introduces well-known consistency issues. This paper puts forward the question about data dependence in data consistency, which embodies pseudo-conflict updates and update dependency. According to that, an optimistic data consistency method is proposed. In our method, data object is partitioned into data blocks by fixed size, as the basic unit of data management. Updates are compressed by Bloom filter technique and propagated in double-path. Negotiation algorithms detect and reconcile update conflicts, and dynamic data management algorithms accommodate dynamic data processing. The results of the performance evaluation show that our method is an efficient method to achieve consistency, good dynamic property, and strong robustness.
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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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
This article assesses the performance of a virtual pheromone-based sectored dispersion algorithm which is implemented on a low-cost miniature mobile robotic platform using sonar sensing. The approach is a distributed ...
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This article assesses the performance of a virtual pheromone-based sectored dispersion algorithm which is implemented on a low-cost miniature mobile robotic platform using sonar sensing. The approach is a distributed one and the robotic platform and sensor array are sufficiently inexpensive that they can be employed in undergraduate research and/or for coursework in a small college environment
The main focuses of the 2nd International Middleware Doctoral Symposium took place at Middleware 2005 are discussed. The symposium is a forum for an invited group of doctoral students and it provides an opportunity fo...
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The main focuses of the 2nd International Middleware Doctoral Symposium took place at Middleware 2005 are discussed. The symposium is a forum for an invited group of doctoral students and it provides an opportunity for them to obtain guidance from mentors and to meet with their peers. The event is aimed to give students constructive criticism before their thesis defense and foster discussions related to future career opportunities. The symposium attracted many high-quality submissions, ensuring a competitive selection process.
The conjugate residual (CR) algorithm is a Krylov subspace algorithm that can be used to obtain fast solutions for symmetric linear systems with very large and very sparse coefficient matrices. By changing the computa...
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The conjugate residual (CR) algorithm is a Krylov subspace algorithm that can be used to obtain fast solutions for symmetric linear systems with very large and very sparse coefficient matrices. By changing the computation sequence in the CR algorithm, this paper proposes an improved Conjugate Residual (ICR) algorithm. The numerical stability of ICR algorithm is same as CR algorithm, but the synchronization overhead that represents the bottleneck of the parallel performance is effectively reduced by a factor of two. And all inner products of a single iteration step are independent and communication time required for inner product can be over lapped efficiently with computation time of vector updates. From the theoretical and experimental analysis it is found that ICR algorithm is faster than CR algorithm as the number of processors in creases. The experiments performed on a 64-processor cluster indicate that ICR is approximately 30% faster than CR.
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