Ruisheng Zhang

Hadoop MapReduce Framework to Implement Molecular Docking of Large-Scale Virtual Screening

Traditional virtual screening in the grid needs chemists to upload small molecule files and collect the results manually, which cannot implement docking and collection of results automatically. This caused heavy workload to chemists. In this paper, we took advantage of Hadoop platform in the massive data storage. We stored and managed small molecule files and docking results files using HDFS. In addition, MapReduce programming framework is used for parallel molecular docking to preliminarily process results files, in order to achieve the automation of the virtual screening molecular docking. The research of this thesis will be helpful to drug researcher by offering a massive data storage management system for large-scale virtual screening, and will also provide a reference for drug discovery in the cloud environment to promote the development of computational chemistry e-science.

Contextualizing scientific workflows in cooperative design

Scientific workflows (SWFs) aim to automate cooperative design through compilation of known sequences of actions for routine procedures. However, current SWF systems lack the ability, in the one hand, to capture the context in which a SWF is designed and developed, and, in the other hand, to deliver a real-time assistance to help designers to make effective decisions in the selection of relevant SWFs for their problem. We propose a context-oriented framework for improving cooperative SWF design. This framework allows making context explicit and realizing the contextualization of SWFs in a SWF repository (and thus sharable with other scientists). Context is made explicit thanks to Contextual Graphs (CxGs), a formalism for representing uniformly all the ingredients of a cooperative SWF design process. Thus, scientists can customize information and formalize their research and strategies in a shared context. We use the context-oriented framework in an application in virtual screening. Finally, context-based formalisms, such as CxGs, appear as the key element to enhance users cooperation during the SWF design phase.

Extending BPEL2.0 for Grid-Based Scientific Workflow Systems

SWF, short for scientific workflow, has recently emerged as a paradigm for orchestrating large-scale e-Science applications. SWF specification connects workflow designer with workflow engine, which makes it act ass one of the key components in SWF systems. We adopted BPEL as the Gird-based SWF specification because of its potential benefits to promote SWF sharing and reproducibility. However, grid-based SWF has unique features, which pure BPEL is not capable to handle. Appropriate ways to extend BPEL to fulfill the special needs should be found. We concluded three most necessary requirements and three kinds of alternative methods to extend BPEL within China Grid Support Platform, and implemented the method of adding additional abstractions upon BPEL to enhance user experience. Our work and findings suggest that our extension approach is feasible and would manifest potential advantage to SWF systems and finally innovate in the e-Science research and applications.

Investigating the Feasibility of Making Contexts Explicit in Designing Cloud Workflow

Cloud workflow allows automating the workflow process through a compilation of known sequences of actions in cloud environment. Current Cloud workflows lack the ability, in the one hand, to capture the contexts during the design phase of Cloud workflows; and in the other hand, to deliver a real-time assistance to help a specific user interact with the system in the selection of the relevant cloud workflow components for his specific need. We propose a context-oriented approach to improve the design phase of cloud workflows. A user-oriented paradigm is presented to make contexts explicit in designing cloud workflows. Context will be made explicit due to the integration of BPEL and Contextual Graphs (CxGs) representation. CxGs representation is the formalism for representing uniformly all the ingredients of design process in cloud workflows, so that users could customize information, formalize their design strategies, and possibly interact with the system to model the cloud workflow. We illustrate our methodology through a case study in virtual screening to testify our investigation study. Finally, we conclude that the method we proposed for making contexts explicit in Cloud workflows could be considered as a successful attempt to address the social and human factors related to the design of Cloud workflows.

A context-based framework for improving decision making in scientific workflow

Scientific workflow (SWF) is considered as a way to automate the decision making with a compilation of known sequences of actions for routine procedure. Current scientific workflow systems lack abilities, in the one hand, in capturing the “context” of the case of the scientific workflow, and, in the other hand, in delivering the real-time assistance to help the user make effective decisions. We propose a context-based framework to improve decision making in SWF. This framework allows making context explicit and realizing the contextualization of the workflows stored in the SWF repository. We use Contextual Graphs (CxGs) as formalism for representing uniformly all the ingredients of a decision-making process in a SWF, so that scientists can customize information and formalize their research and strategies. An example drawn from an application in virtual screening is given to illustrate the potentiality of our context-based framework. Finally, we conclude that a context-based formalism such as CxGs is the key element to enhance decision-making support in SWF systems.

Context-oriented scientific workflow system and its application in virtual screening

Scientific workflow (SWF) system is gradually liberating the computational scientists from burden of data-centric operations to concentration on their decision making. However, contemporary SWF systems fail to address the variables when scientists urge to deliver new outcomes through reproduction of workflow, including not only workflow representation, but also its “context” of use. Thus, current failure is mainly due to lack of representing and managing the “context”. We propose a context-oriented approach to create a SWF system more adaptive to the dynamic research environment. We present the feedbacks from interviews of multi-national virtual screening scientists, and illustrate a case study in which their decision making processes are modelled by contextual graphs as a uniform representation of knowledge, of reasoning, and of contexts. Finally, we conclude and highlight that sharing SWF intellectually with its context would make SWF as a complement to paper-based publications.

An Improved Visual BPEL-Based Environment for Scientific Workflow

Scientists are increasingly using scientific workflow environment to manage large data sets and execute experiments on distributed resources. Scientific workflows have become an important mechanism for scientists to combine scientific data management, analysis, simulation, and visualization tasks. However, most of the environments dont fully hide the complexity of the underlying orchestration language and middleware. Whats more, almost all environments only provide a graphical editor but do nothing to offer a programmatic environment to scientists with the knowledge of the programming. In this paper, we introduce an improved scientific workflow environment called SWFVD to solve these problems by isolating visual representation from translation visual representation to business process execution language (BPEL). Meanwhile, we add some tool support for scientist to deal with BPEL to make the whole environment more convenient. The prototype of SWFVD based on China gird supporting platform (CGSP) is also given and examplesfrom chemistry are presented.

A rule-based agent-oriented approach for supporting weakly-structured scientific workflows

Weakly-structured Scientific Workflows (WsSWFs) often contain goal-oriented tasks that are logical and complicated, but they are vital for workflow results. They may involve interactions between multiple participants or have complicated logic to express scientific policies and cater to dynamic execution environments. In general, such WsSWFs not only need a rich process and (domain-specific) decision logic specification, but also require a flexible execution and human interaction. In this paper, we propose a Rule-based Agent-oriented Framework (RbAF) to support the WsSWF execution by combining rule-based knowledge representation with agent technology. We describe workflows by messaging reaction rules, which go beyond global Event-Condition-Action (ECA) rules and support performing complex actions locally within certain contexts. We describe (domain-specific) decision logic in workflows by exploiting the benefits of both Logic Programming (LP) and Description Logic (DL). Our evaluation results show that, RbAF well supports the WsSWFs and has higher expressive power than other three considered scientific workflow systems.

A Visual Scientific Workflow Designer for Chemists in Grid Environment

Scientific workflows are becoming increasingly important as a mechanism for orchestrating distributed resources such as computational devices, data, applications, and scientific instruments on the grid environment. BPEL is generally accepted as a de-facto standard for web-services composition. However, the lack of generic graphical interfaces that abstract the technical details for domain scientists has gradually become a major obstacle for them to easily master the workflow systems. This paper discusses our visual scientific workflow designer for Chemical e-Science Studies in the Grid environment. The designer is based on the ChinaGrid Support Platform (CGSP), and it allows scientists to compose the scientific workflow with a graphical representation of the BPEL specification by simply dragging and dropping the graphical elements within a canvas. We applied the designer to a Chemical case study and demonstrated the flexibility and simplicity for composing scientific workflows.

Integrating Heterogeneous Grid Middleware to Support Large-Scale Bag-of-Tasks Applications

Bag-of-Tasks (BoTs) applications are loosely coupled parallel applications whose concurrent entities are independent of each other. In this paper, we propose a novel architecture, which integrates distributed resources across heterogeneous Grid systems to support large-scale BoT applications. We present our integration solution and introduce how our prototype is implemented. Finally, we demonstrate our solution with a use case from the domain of drug discovery. It turns out that our proposal not only provides an adequate tool to support the development of BoT applications, but also is coherent and operationally reliable.