FedGrid: An HLA Approach to Federating Grids
Research on Grids has received considerable attention in recent years. Whereas existing work on connecting the grids primarily focused on grid services, in our work we propose a unified approach, so-called FederationGrid (or FedGrid for short), which integrates both virtual organization (VO) and grid services, thus enabling formation of virtual communities on top of grids. FedGrid is based on the standard High Level Architecture (HLA) that enjoys the advantages of high-level information modeling, including re-usability of software components and real-time performance of the overall systems. In addition, FedGrid is a fractal grid, comprised of hierarchical HLA federations, e.g. Realms and Lobby, which supports well the concept of virtual communities and scalability.

title: An efficient clustered architecture for P2P networks
abstract: Peer-to-peer (P2P) computing offers many attractive features, such as self-organization, load-balancing, availability, fault tolerance, and anonymity. However, it also faces some serious challenges. In this paper, we propose an Efficient Clustered Super-Peer P2P architecture (ECSP) to overcome the scalability and efficiency problems of existing unstructured P2P system. With ECSP, peers are grouped into clusters according to their topological proximity, and super-peers are selected from regular peers to act as cluster leaders and service providers. These super-peers are also connected to each other, forming a backbone overlay network operating as a distinct, yet integrated, application. To maintain the dynamically adaptive overlay network and to manage the routing on it, we propose an application level broadcasting protocol: Efa. Applying only a small amount of information about the topology of a network, Efa is as simple as flooding, a conventional method used in unstructured P2P systems. By eliminating many duplicated messages, Efa is much more efficient and scalable than flooding, and furthermore, it is completely decentralized and self-organized. Our experimental results prove that ESCP architecture, combined with the super-peer backbone protocol, can generate impressive levels of performance and scalability.

title: Cycles Containing Given Subsets in 1-Tough Graphs

title: Towards evolving Web sites into grid services environment
abstract: Grid services are emerged by integrating grid computing and Web services to perform a seamless information processing system across distributed, heterogeneous, dynamic virtual organisations that the user can access from any location. The Web Service Resource Framework (WSRF) was announced as a new way for manipulating "stateful resources" to perform grid services. It defines the concept of "stateful resources" and how they can be discovered, queried and manipulated via Web services. In this paper, we proposed a grid services-oriented reengineering approach to create stateful resources from conventional HTML Web sites, which applies hierarchical cluster and wrapper techniques to extract and translate Web sites resources. It supports services identification and packaging and archives Web site evolution into grid services environment by exploiting WRSF.

title: High-order Compact Schemes for Nonlinear Dispersive Waves
abstract: High-order compact finite difference schemes coupled with high-order low-pass filter and the classical fourth-order Runge–Kutta scheme are applied to simulate nonlinear dispersive wave propagation problems described the Korteweg-de Vries (KdV)-like equations, which involve a third derivative term. Several examples such as KdV equation, and KdV-Burgers equation are presented and the solutions obtained are compared with some other numerical methods. Computational results demonstrate that high-order compact schemes work very well for problems involving a third derivative term.

title: Probabilistic models for discovering e-communities
abstract: The increasing amount of communication between individuals in e-formats (e.g. email, Instant messaging and the Web) has motivated computational research in social network analysis (SNA). Previous work in SNA has emphasized the social network (SN) topology measured by communication frequencies while ignoring the semantic information in SNs. In this paper, we propose two generative Bayesian models for semantic community discovery in SNs, combining probabilistic modeling with community detection in SNs. To simulate the generative models, an EnF-Gibbs sampling algorithm is proposed to address the efficiency and performance problems of traditional methods. Experimental studies on Enron email corpus show that our approach successfully detects the communities of individuals and in addition provides semantic topic descriptions of these communities.

title: Mining the smallest association rule set for predictions
abstract: Mining transaction databases for association rules usually generates a large number of rules, most of which are unnecessary when used for subsequent prediction. In this paper we define a rule set for a given transaction database that is much smaller than the association rule set but makes the same predictions as the association rule set by the confidence priority. We call this subset the informative rule set. The informative rule set is not constrained to particular target items; and it is smaller than the non-redundant association rule set. We present an algorithm to directly generate the informative rule set, i.e., without generating all frequent itemsets first, and that accesses the database less often than other unconstrained direct methods. We show experimentally that the informative rule set is much smaller than both the association rule set and the non-redundant association rule set, and that it can be generated more efficiently.