Meilin Shi

Build grid-enabled large-scale collaboration environment in e-Learning grid

Abstract As a new branch of grid computing, e-Learning grid is emerging as a nationwide e-Learning infrastructure, which can provide innovative learning experience for learners. In such a grid environment, collaboration services will be the key elements due to the pervasive requirement for cooperative work and collaborative learning. Although there exist enormous research efforts on grid-based collaboration technologies, most of them have many limitations. In this paper, with the findings from the computer support cooperative work (CSCW)/computer support collaborative learning (CSCL) and advantages provided by grid, we propose to build grid-enabled large-scale collaboration environment (GLCE). GLCE focuses on distributed, large-scale, and cross-organizational collaboration through creating group-centered next generation collaboration environment, where both intra-group and inter-group collaboration could be supported. With this idea in mind, we present a grid-based cooperative work framework (GCWF), which aims to implement GLCE with an “upper layer” collaboration middleware based on the special-purpose grid infrastructure designed by our team. The preliminary results of our research on GLCE have been applied to build the learning assessment grid (LAGrid). The goal of LAGrid is to support the formative assessment business in China Radio and TV University (CRTVU) and large-scale collaboration within virtual organization (VO) has been realized.

A Context Model for Collaborative Environment

Context awareness, context sharing and context processing are key requirements for the future CSCW, HCI and ubiquitous computing systems. Until now, the collaborative context factors have been seldom specifically addressed. This paper argues that a generic context model is very important for building context-aware collaborative applications. A new semantic rich context model for collaborative environment is proposed. The conceptual model for context is described as ontology for contextual collaborative applications (OCCA). The model for context query & memory service, context matching service and control policies is illustrated. Information space, interaction space and collaboration control mechanisms are built up or implemented based on this context model

CovaTM: a transaction model for cooperative applications

It has been widely recognized that traditional transaction models with ACID(Atomicity, Consistency, Isolation and Durability) properties generally are not applicable to cooperative applications. Though many advanced transaction models have been proposed to address the problems, they are too database-centered or too rigid to be useful in real environments. This paper presents a new transaction model named CovaTM, which provides sophisticated but flexible control over cooperative process as well as support for error recovery and exception handling. The most distinguished feature of this model is that user intervention is explicitly introduced into transaction processing. This paper details the features and structural elements of this model. An example is also given to illustrate how it works in real world settings.

Modeling contexts in collaborative environment: a new approach

Context awareness, context sharing and context processing are key requirements for the future CSCW, HCI and Ubiquitous computing systems. However, research issues of collaborative context have not been completely addressed till now. While arguing that a generic context model is very important for building context-aware collaborative applications, this paper proposes a new semantic rich context modeling approach, Ontology for Contextual Collaborative Applications (OCCA), for collaborative environments. Based on OCCA, mechanisms for context query, context matching and collaboration awareness control are devised using semantic query and reasoning technology to support the three perspectives of a context model, i.e., information space, interaction space and collaboration control. We present an evaluation study on the features and performance of OCCA and context query services.

A Scalable Framework for Large-Scale Distributed Collaboration

There is an increasing need for computer-supported cooperative work (CSCW) in recent years. However, most of existing collaborative systems are not scalable enough, thus leading to bad usability. In this paper we propose a scalable framework for large-scale distributed collaboration which aims to support a wide range of collaboration requirements. The framework comprises a set of geographically dispersed collaborative servers (co-servers) specially deployed by participant organizations. The set of co-servers constitutes an overlay network which provides an infrastructural supporting environment for large-scale distributed collaboration. The framework is scalable in terms of the geographic distribution of participant organizations, size of groups, and total number of groups. The framework will be used to build the next-generation collaborative e-learning platform. A prototype system is being developed to demonstrate the application of the framework

An agent-based framework for cross-domain cooperation of virtual enterprise

Researchers on virtual enterprise cooperation have tried to implement the cross-domain cooperation and inner-domain cooperation of virtual enterprise using an identical method. Based on the analysis of why agent-based mechanism is suitable and only suitable for cross-domain cooperation of virtual enterprise, we propose a framework to implement it. In our framework, there is a service information Supply-Demand Center (SDC) which is in charge of service information management and agent is responsible for cooperative partner selecting before cooperation and interaction during cooperation. The relevant key strategies and basic interaction models are also described. Finally, application of the framework in ECCS (e-commerce based cooperative system) and Webflow - which are our two workflow-based cooperative systems - is introduced.

CoFrame: a framework for CSCW applications based on grid and Web services

Though 20 years have passed since the birth of CSCW, the original goal of it is not reached as well as people expected. This situation is mostly due to the supporting technology especially the infrastructure. Today, great changes have taken place in technology, including grid computing and Web services. These technologies, we think, significantly affect the application of CSCW. In this paper, a framework called CoFrame is proposed to answer the challenges faced by CSCW. Based on the emerging grid and Web service technologies, CoFrame provides some general yet flexible cooperation related services and organizes them into different layers. The elaborately designed services and architecture make CoFrame adaptive to diverse requirements of different domains. The paper details the framework and demonstrates its application with a case study in e-learning.

Research on grid-based cooperative platform

Cooperative work support is one goal of grid computing, according to the requirements for cooperative work support in different community, the paper proposes a CSCW-oriented grid architecture using service oriented architecture (SOA) approach. Based on the architecture, learning assessment grid (LAGrid) is designed and deployed for business of formative assessment within China Central Radio & TV University (CCRTVU), and the grid provides environment for large-scale collaboration.

Pattern-Oriented Planning Approach for Grid Workflow Generation

As the key enabling technology for grid perspective, grid workflow receives more and more attention of researchers and has been applied to many projects. Dynamic workflow generation is considered as one of the most important issues in grid workflow researches, because it has essential impact on system usability, flexibility and robustness. Currently, exploiting AI planning technology for workflow construction is emerging in some researches. Although it works well in specific problem domain, the lack of explicit knowledge jeopardizes its scalability and significance in grid workflow. In this work, we put forward process pattern as a vehicle for knowledge representation to capture process expertise in business level, and based on it, a planning approach is proposed for automated workflow generation; Compared with existing planning method, our pattern-oriented approach minimizes user-visible complexity and makes system more scalable and flexible by utilizing explicit knowledge support

Knowledge modeling and optimization in pattern-oriented workflow generation

Automatic workflow generation is becoming an active research area for dealing with the dynamics of grid infrastructure. Artificial intelligence technology and explicit knowledge have been exploited in some research works for workflow construction or composition. With the increasing popularity of knowledge, its quality has growing impact on system performance. This paper proposed a synthesis method of pattern knowledge modeling and optimization for pattern based workflow generation planning. Experts define the primary modeling, and then the subsequent classifier training adjusts and improves the pattern knowledge settings. The experiments and application demonstrate that this approach can substantially reduce the modeling difficulties and effectively improve pattern knowledge quality.