Grid resource discovery based on semantic P2P communities
Grid technologies enable the sharing of a wide variety of resources. The full use of these resources requires effective resource discovery mechanisms. However, the complicated and dynamic characteristics of grid resources make sharing and discovering them a challenge. In this paper, we propose a semantic community approach to enable efficient resource discovery in grids. The system clusters nodes into communities according to their semantic properties. The community construction and maintenance is fully decentralized and self-organizing. This structure helps prune the searching space and reduce the cost of searching. The system exhibits many desirable properties: it supports complex queries and is fully decentralized, scalable, and efficient. Our simulation results show how searching the grids can take advantage of semantic communities to reduce searching costs and improve the quality of results.

title: ECSP: An Efficient Cluster Based P2P Architecture

title: Grid Resource Discovery Using Semantic Communities
abstract: Grid technologies enable the sharing and collaborating of a wide variety of resources. To fully utilize these resources, effective resource discovery mechanisms are necessities. However, the complicated and dynamic characteristics of the grid resources make sharing and discovering them a challenging issue. In this paper, we propose a semantic community approach to assisting the efficient resource discovery and query in grids. Semantic community is a natural arrangement of distributed systems. It prunes the searching space and reduces the cost of searching. Moreover, it exhibits many desirable properties, including being fully decentralized and supporting complex queries. Our simulation results show how searching the girds can take advantage of semantic communities to reduce the searching cost and improve the quality of search results.

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: FedGrid: An HLA Approach to Federating Grids
abstract: 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: Efa: an efficient content routing algorithm in large peer-to-peer overlay networks
abstract: An important issue for peer-to-peer application is to locate content within the network. There are many existing solutions to this problem, however, each of them addresses different aspects and each has its deficiencies. We focus on the unstructured peer-to-peer scenario and present a constrained flooding routing algorithm, Efa, which overcomes some of the deficiencies of those existing strategies. Efa performs application level broadcasting in a potentially very large peer-to-peer network overlaid on the Internet. Efa is completely decentralized and self-organized. It is a more scalable alternative to flooding, which is commonly used in unstructured peer-to-peer systems. Utilizing just a small amount of topology info, Efa is almost as simple as flooding, but it is much more efficient and scalable.

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: 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: A grid oriented approach to reusing legacy code in ICENI framework
abstract: Legacy systems are valuable assets for organisations. They continuously evolve with new emerged technologies in rapidly changing business environment. ICENI provided an excellent grid middleware framework for developing grid-based systems. It creates an opportunity for legacy systems to evolve in grid environment. In this paper, we propose a component-based reengineering approach which applies software clustering techniques and program slicing techniques to recover components from legacy systems. It supports component encapsulation with JNI and component integration with CXML. The resulting components with core legacy code function in grid environment.

title: Scalable audio streaming over the internet with network-aware rate-distortion optimization
abstract: Reliable audio streaming over the unreliable Internet is a challenging task. Because during a connected session, the bandwidth can vary greatly and the data packets can be lost in the transmission, it is difficult to guarantee a smooth quality of the delivered audio over the Internet. In this work, a system for streaming of scalable coded audio over the Internet is proposed. Scalable audio coding generates a bitstream consisting a number of data units (DUs), where a subset of the DUs can be extracted to reconstruct audio at a lower quality level. A network aware ratedistortion optimization model is proposed so that the server can easily adapt to the network bandwidth fluctuation by sending less packets when the network is congested. The server can also deal with severe packet loss by only retransmitting the more important data packets. By using the scalable audio coding and network aware delivery scheme, the quality of the audio streaming over severe network condition is improved dramatically.

title: Securing distributed adaptation
abstract: Open architecture networks provide applications with fine-grained control over network elements. With this control comes the risk of misuse and new challenges to security beyond those present in conventional networks. One particular security requirement is the ability of applications to protect the secrecy and integrity of transmitted data while still allowing trusted active elements within the network to operate on that data. This paper describes mechanisms for identifying trusted nodes within a network and securely deploying adaptation instructions to those nodes while protecting application data from unauthorized access and modification. Promising experimental results of our implementation within the conductor adaptation framework are also presented, suggesting that such features can be incorporated into real networks.