Jianwu Wang

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Service composition is becoming the dominant paradigm for developing Web service applications. It is important to ensure that a service composition complies with the requirements for the application. A rigorous compliance checking approach usually needs the requirements being specified in property specification formalisms such as temporal logics, which are(More)
MapReduce provides a parallel and scalable programming model for data-intensive business and scientific applications. MapReduce and its de facto open source project, called Hadoop, support parallel processing on large datasets with capabilities including automatic data partitioning and distribution, load balancing, and fault tolerance management. Meanwhile,(More)
Next-generation DNA sequencing machines are generating a very large amount of sequence data with applications in many scientific challenges and placing unprecedented demands on traditional single-processor bioinformatics algorithms. Middleware and technologies for scientific workflows and data-intensive computing promise new capabilities to enable rapid(More)
End-user service composition is a promising way to ensure flexible, quick and personalized information provision and utilization, and consequently to better cope with spontaneous business requirements. For end-users to compose services directly, issues like service granularity, service organization and business-level semantics are critical. End-users will(More)
With the increasing popularity of the Cloud computing, there are more and more requirements for scientific work-flows to utilize Cloud resources. In this paper, we present our preliminary work and experiences on enabling the interaction between the Kepler scientific workflow system and the Amazon Elastic Compute Cloud (EC2). A set of EC2 actors and Kepler(More)
In the Big Data era, workflow systems need to embrace data parallel computing techniques for efficient data analysis and analytics. We present an easy-to-use, scalable approach to build and execute Big Data applications using actor-oriented modeling in data parallel computing. We use two bioinformatics use cases for next-generation sequencing data analysis(More)
Raising end-user's programmability is a promising way to ensure more flexible and higher-quality information provision and utilization, and to better cope with spontaneous business requirements as well. This paper presents the state-of-the-art developments of the end-user service composition language VINCA and its corresponding approach to developing(More)
Distributed Data-Parallel (DDP) patterns such as MapReduce have become increasingly popular as solutions to facilitate data-intensive applications, resulting in a number of systems supporting DDP workflows. Yet, applications or workflows built using these patterns are usually tightly-coupled with the underlying DDP execution engine they select. We present a(More)
Large-scale production of biopharmaceuticals by current bioreactor techniques is limited by low transgenic efficiency and low expression of foreign proteins. In general, a bacterial artificial chromosome (BAC) harboring most regulatory elements is capable of overcoming the limitations, but transferring BAC into donor cells is difficult. We describe here the(More)
This paper introduces a novel service modeling approach called VINCA_BS, which can be used by business people to extend the functionality of a service-based software platform from a business perspective. VINCA_BS approach introduces the domain analysis approaches into service modeling and uses the domain requirement commonalities to define our VINCA(More)