From Semantic Grid to knowledge service cloud

The World Wide Web is a major breakthrough in the history of human communication and information sharing (Berners-Lee et al., 2006). The Web has brought us a series of revolutionary tools, such as digital libraries, net meetings, e-mails, and data services, which have changed the face of scientific research and publishing. Scientists are increasingly relying on these tools to conduct their daily research, and to collaborate with their colleagues through distant communication and knowledge sharing. Despite all these accomplishments, there are still gaps between what can be done using the current Web and what need to be done in an e-Science environment (Buetow, 2005). Computer scientists have long envisioned a ‘cyberinfrastructure for e-Science’ on top of the current Web infrastructure (Hey and Trefethen, 2005). Wright and Wang (2011) stated that cyberinfrastructure “integrates advanced computer, information, and communication technologies to empower computation-based and data-driven scientific practice and improve the synthesis and analysis of scientific data in a collaborative and shared fashion”. Various approaches have been taken to build such a cyberinfrastructure, including service-oriented computing (Papazoglou and Georgakopoulos, 2003; Bichier and Lin, 2006), Grid computing (Foster, 2002), and cloud computing (Armbrust et al., 2010). Computer scientists have advocated serviceoriented approaches to e-Science for years (Foster, 2005). Papazoglou and Georgakopoulos (2003) defined service-oriented computing (SOC) as “the computing paradigm that utilizes services as fundamental elements for developing applications”. The application of SOC on the Web is manifested by Web services, which enable application programs to communicate in ways that are independent of specific platforms and languages, and therefore facilitate system interoperability (Papazoglou and Georgakopoulos, 2003). Web services can be used to implement a cyberinfrastructure according to ServiceOriented Architecture (SOA), which turns the development of e-Science applications into a pipeline of service development, service deployment, and service combination (Erl, 2008). As an extension to SOC, Grid computing is also a major approach to building the cyberinfrastructure for e-Science (Foster, 2002). In essence, a Grid computing environment enables the integration of services and resources across distributed, heterogeneous, dynamic virtual organizations (Foster et al., 2002). The most famous solution to Grid computing is the Globus Toolkit, which is an open source set of services and software libraries that support Grids and Grid applications (Foster, 2006). Grids have been successfully applied in many e-Science projects covering various areas of science, engineering, and medicine (Hey and Trefethen, 2005). In addition to Grid computing, cloud computing is also a popular paradigm of distributed computing characterized by the delivery of storage capacity, computational capacity, and software as Web services, and the decoupling of service delivery from underlying technology (Armbrust et al., 2010). Cloud computing has arisen from the improvements in software abstractions that hide the complexity of Journal of Zhejiang University-SCIENCE C (Computers & Electronics) ISSN 1869-1951 (Print); ISSN 1869-196X (Online) www.zju.edu.cn/jzus; www.springerlink. com E-mail: jzus@zju.edu.cn