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Front. Inform. Technol. Electron. Eng.  2012, Vol. 13 Issue (4): 253-256    DOI: 10.1631/jzus.C1101006
    
From Semantic Grid to Knowledge Service Cloud
Zhao-hui Wu, Hua-jun Chen
School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
From Semantic Grid to Knowledge Service Cloud
Zhao-hui Wu, Hua-jun Chen
School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
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摘要： According to Foster et al. (2008), Grid computing and cloud computing are closely related paradigms that share a lot of commonality in their vision, architecture, and technology. They also share some limitations, namely the inability to provide intelligent and autonomous services, the incompetency to address the heterogeneity of systems and data, and the lack of machine-understandable content. Mika and Tummarello (2008) identified the root cause of these limitations as the lack of ‘Web semantics’.
The Semantic Web is an emerging technical movement target on Web semantics (Berners-Lee et al., 2006). The Semantic Web languages, such as Resource Description Framework (RDF), RDF Schema (RDFS), Web Ontology Language (OWL), and SPARQL, together with a rich set of pragmatic tools, enable a Web of data with semantics formally defined (Domingue et al., 2011). The reliability, effectiveness, and efficiency of these technologies have been proved in practical applications from various domains such as biology, medical science, healthcare, and pharmaceutics. As Semantic Web technologies are reaching maturity, computer scientists are exploring the possibilities of integrating Semantic Web technologies into other Web-based technologies (e.g., SOC, Grid computing, and cloud computing), to create more powerful integration solutions. In this paper, we will discuss three major trends of technical integration: Semantic Web Services (Payne and Lassila, 2004), the Semantic Grid (de Roure et al., 2001), and the Knowledge Service Cloud (KSC).
Abstract: According to Foster et al. (2008), Grid computing and cloud computing are closely related paradigms that share a lot of commonality in their vision, architecture, and technology. They also share some limitations, namely the inability to provide intelligent and autonomous services, the incompetency to address the heterogeneity of systems and data, and the lack of machine-understandable content. Mika and Tummarello (2008) identified the root cause of these limitations as the lack of ‘Web semantics’.
The Semantic Web is an emerging technical movement target on Web semantics (Berners-Lee et al., 2006). The Semantic Web languages, such as Resource Description Framework (RDF), RDF Schema (RDFS), Web Ontology Language (OWL), and SPARQL, together with a rich set of pragmatic tools, enable a Web of data with semantics formally defined (Domingue et al., 2011). The reliability, effectiveness, and efficiency of these technologies have been proved in practical applications from various domains such as biology, medical science, healthcare, and pharmaceutics. As Semantic Web technologies are reaching maturity, computer scientists are exploring the possibilities of integrating Semantic Web technologies into other Web-based technologies (e.g., SOC, Grid computing, and cloud computing), to create more powerful integration solutions. In this paper, we will discuss three major trends of technical integration: Semantic Web Services (Payne and Lassila, 2004), the Semantic Grid (de Roure et al., 2001), and the Knowledge Service Cloud (KSC).
出版日期: 2012-04-07
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Zhao-hui Wu
Hua-jun Chen

引用本文:

Zhao-hui Wu, Hua-jun Chen. From Semantic Grid to Knowledge Service Cloud. Front. Inform. Technol. Electron. Eng., 2012, 13(4): 253-256.

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http://www.zjujournals.com/xueshu/fitee/CN/10.1631/jzus.C1101006    或    http://www.zjujournals.com/xueshu/fitee/CN/Y2012/V13/I4/253

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