Zhenchun Huang

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Recently IT giants such as Google, Amazon, Microsoft, and IBM are gearing up to be a part of the Cloud and begin to sell their cloud services. However, the current market trading mechanism is inflexible, and the price is not reasonable enough in some situation. Therefore, we first propose a cloud market framework for people to build a uniform and fully(More)
Service oriented architecture becomes the mainstream of grid research today. On-demand service, which can provides better flexibility for grid users, is purposed in this paper. According to the research on different implementation policies, on-demand service architectures for virtual machine based on-demand service and service specification reference based(More)
In the previous years, service oriented architecture and its most famous implementation known as Web service are more and more popular and adopted by many distributed computing systems. The spatial information processing applications are eager for SOA based on-demand computation framework with high performance and low overhead. In this paper, the(More)
The target of Grid monitoring and management is to monitor services in Grid for fault detection, performance analysis, performance tuning, load balancing and scheduling. This paper introduces the design and implementation of a WSLA-based Grid monitoring and management system--GSMon. In GSMon, we use a service-oriented architecture, give the monitoring(More)
Data grid is powerful for distributed data sharing and collaborating, which is very important for the spatial information applications. But the difference among meta-data produced by space agencies around the world makes it difficult to re-organize data and share them. In this paper, a way named meta-data adapter is proposed, which can interpreter original(More)
With the continuously growing data from scientific devices and models, data exploration becomes one of four kinds of scientific research paradigms. It leads to faster, larger-scale and more complex processing requirements, and parallelism is being more and more important for scientific data analyzing applications. But, because of troubles such as unstable(More)