Grids enable users to share and access large collections and various types of resources in wide areas, and how to locate resources in such dynamic, heterogeneous and autonomous distributed environments is a key and challenging issue. In this paper, a three-level decentralized and dynamic VEGA Infrastructure for Resource Discovery (VIRD) is proposed. In this architecture, every Border Grid Resource Name Server (BGRNS) or Grid Resource Name Server (GRNS) has its own local policies, governing information organization, management and searching. Changes in resource information are propagated dynamically among GRNS servers according to a link-state-like algorithm. A client can query its designated GRNS either recursively or iteratively. Optimizing techniques, such as shortcut, are adopted to make the dynamic framework more flexible and efficient. A simulator called SimVIRD is developed to verify the proposed architecture and algorithms. Experiment results indicate that this architecture could deliver good scalability and performance for grid resource discovery.

"Grid" computing has emerged as an important new research field. With years of efforts, grid researchers have successfully developed grid technologies including security solutions, resource management protocols, information query protocols, and data management services. However, as the ultimate goal of grid computing is to design an infrastructure which supports dynamic, cross-organizational resource sharing, there is a need of solutions for efficient and transparent task re-scheduling in the grid. In this research, a new grid middleware is proposed, called G-JavaMPI. This middleware adds the parallel computing capability of Java to the grid with the support of a Grid-enabled message passing interface (MPI) for inter-process communication between Java processes executed at different grid points. A special feature of the proposed G-JavaMPI is the support of Java process migration with post-migration message redirection. With these supports, it is possible to migrate executing Java process from site to site for continuous computation, if some site is scheduled to be turned down for system reconfiguration. Moreover, the proposed G-JavaMPI middleware is very portable since it requires no modification of underlying OS, Java virtual machine, and MPI package. Preliminary performance tests have been conducted. The proposed mechanisms have shown good migration efficiency in a simulated grid environment.

The current grid security research is mainly focused on the authentication of grid systems. A problem to be solved by grid systems is to ensure consistent access control. This problem is complicated because the hosts in a grid computing environment usually span multiple autonomous administrative domains. This paper presents a grid access control model, based on asynchronous automata theory and the classic Bell-LaPadula model. This model is useful to formally study the confidentiality and integrity problems in a grid computing environment. A theorem is proved, which gives the necessary and sufficient conditions to a grid to maintain confidentiality. These conditions are the formalized descriptions of local (node) relations or relationship between grid subjects and node subjects.

Spatial applications will gain high complexity as the volume of spatial data increases rapidly. A suitable data processing and computing infrastructure for spatial applications needs to be established. Over the past decade, grid has become a powerful computing environment for data intensive and computing intensive applications. Integrating grid computing with spatial data processing technology, the authors designed a spatial data processing grid (called SDPG) to address the related problems. Requirements of spatial applications are examined and the architecture of SDPG is described in this paper. Key technologies for implementing SDPG are discussed with emphasis.

Grid computing emerges as effective technologies to couple geographically distributed resources and solve large-scale computational problems in wide area networks. The fault tolerance is a significant and complex issue in grid computing systems. Various techniques have been investigated to detect and correct faults in distributed computing systems. Unreliable fault detection is one of the most effective techniques. Globus as a grid middleware manages resources in a wide area network. The Globus fault detection service uses the well-known techniques based on unreliable fault detectors to detect and report component failures. However, more powerful techniques are required to detect and correct both system-level and application-level faults in a grid system, and a convenient toolkit is also needed to maintain the consistency in the grid. A fault-tolerant grid platform (FTGP) based on an unreliable fault detector and the Globus fault detection service is presented in this paper. The platform offers effective strategies in such three aspects as grid key components, user tasks, and high-level applications.

This paper presents an innovative method to synchronize physical clocks for a computational grid, in particular for a computational grid linked through the asynchronous Intranet or Internet environments. The method discussed is an asynchronous self-adaptive clock synchronization mechanism. Two strategies for clock synchronisation are introduced. (1) Use continuous time intervals to calculate the precision of clocks, which can reduce the effect of network delay efficiently. (2) Every node synchronizes its clock with its leader actively. In addition, a node self-adaptive model is presented, and the relationship between the clock precision and synchronization time is induced, hence a node can predict when it should begin the synchronization process. Detailed simulation and extension of this issue are provided at the end of the paper. The presented model is both practical and feasible.

Task scheduling is an integrated component of computing. With the emergence of Grid and ubiquitous computing, new challenges appear in task scheduling based on properties such as security, quality of service, and lack of central control within distributed administrative domains. A Grid task scheduling framework must be able to deal with these issues. One of the goals of Grid task scheduling is to achieve high system throughput while matching applications with the available computing resources. This matching of resources in a non-deterministically shared heterogeneous environment leads to concerns over Quality of Service (QoS). In this paper a novel QoS guided task scheduling algorithm for Grid computing is introduced. The proposed novel algorithm is based on a general adaptive scheduling heuristics that includes QoS guidance. The algorithm is evaluated within a simulated Grid environment. The experimental results show that the new QoS guided Min-Min heuristic can lead to significant performance gain for a variety of applications. The approach is compared with others based on the quality of the prediction formulated by inaccurate information.

Peer-to-Peer (P2P) systems have attracted much attention in academic community and industry circles due to their promising applications in various domains. This paper presents the authors' research efforts on introducing complex query capabilities in a P2P environment consisting of numerous peers with large volume of data. An underlying hybrid P2P computing platform, named BestPeer is described first. The connection among peers within BestPeer is self-configurable through maintaining the nearest neighbor of peers, and the agent techniques employed in the system ensure its capability of providing sophisticated services. The designs of three P2P data management systems which are all based on BestPeer are described in detail. They provide support for information retrieval, query processing and Web services respectively. Advantages and limitations are discussed, while ongoing work is presented. Current systems can provide basic functions for keyword-based search, SQL-like query processing, and Web services querying and discovery. Some further topics on providing fully-fledged data management functionalities for P2P distributed computing systems with security guarantee are also discussed.

The emergence of semantic web will result in an enormous amount of knowledge base resources on the web. In this paper, a generic Knowledge Base Grid Architecture (KB-Grid) for building large-scale knowledge systems on the semantic web is presented. KB-Grid suggests a paradigm that emphasizes how to organize, discover, utilize, and manage web knowledge base resources. Four principal components are under development: a semantic browser for retrieving and browsing semantically enriched information, a knowledge server acting as the web container for knowledge, an ontology server for managing web ontologies, and a knowledge base directory server acting as the registry and catalog of KBs. Also a referential model of knowledge service and the mechanisms required for semantic communication within KB-Grid are defined. To verify the design rationale underlying the KB-Grid, an implementation of Traditional Chinese Medicine (TCM) is described.

This paper presents DSI, a distributed service discovery and integration utility for service grid. The goal of DSI is efficiently to improve service publishing, deletion and lookup, decentralized control, scalability, and availability. DSI comprises a logically global metadata pool and a double-layered DHT (Distributed Hash Table). Efficient service publishing and lookup are achieved by adopting DHT. Clean service deletion is guaranteed by time-stamping. And system availability is improved by replication combined with automatic indexer selection. Experiments show that DSI can achieve short response time, low processing cost and high availability.

Aiming at building up more powerful, open-standard-based and generic infrastructures for application integration, service grids address the challenges in large-scale coordinated sharing and on-demand composition of network-based application services. The related endeavors have opened up new ways of application development, deployment and integration. In connection with the new level of scale, openness and dynamism brought forward by service grids, adaptive service configuration is of essential importance to applications. This paper proposes an approach called CAFISE, which tries to better facilitate on-demand configuration and dynamic reconfiguration of service grid applications. In CAFISE, a business design and its supporting software system are considered in a coherent way, and a convergent relation, which helps to map business-level configurations to software-level configurations, is highlighted. The paper is particularly devoted to presenting and discussing the principles, reference model, modeling language and supporting application framework of CAFISE. Since practical usefulness is highly valued in the development of CAFISE, the application of the approach to a real-world scenario is also presented in the paper.

A cooperative platform called Cova is presented, which aims to uniformly model a wide range of cooperation scenarios and to reduce the groupware design and development work. To achieve these goals, Cova provides two facilities, namely a specification language for developers to describe various cooperation modes uniformly and a run-time system that provides some general-purposed services guaranteeing the semantics specified. With these facilities, the developers can then concentrate on the application specific functions rather than the control mechanisms. Therefore, the development efficiency is promoted. This paper details the design and implementation issues of the platform including the model and the specification language, platform architecture, transaction management, service integration and so on. Application development with Cova platform is also covered.