Ontology-Based Clustering and Routing in Peer-to-Peer Networks
How to improve the performance of content searching in peer-to-peer (P2P) systems is a challenging issue. In this paper we attack this problem by proposing a new decentralized P2P architecture – ontology-based community overlays. The system exploits the semantic property of the content in the network to cluster nodes sharing similar interest together to improve the query and searching performance. Specifically, a distributed hash table (DHT) based overlay is constructed to assist peers organizing into communities. Those peers in the same community form a Gnutella-like unstructured overlay. This architecture helps reduce the search time and decrease the network traffic by minimizing the number of messages propagated in the system. Moreover, it retains the desirable properties of existing unstructured architectures, including being fully decentralized with loose structure, and supporting complex queries. We demonstrate by simulation, that with this architecture, peers can get more relevant resources faster and with less traffic generated.

title: ECSP: An Efficient Cluster Based P2P Architecture

title: OntSum: A Semantic Query Routing Scheme in P2P Networks Based on Concise Ontology Indexing
abstract: Locating desirable resources is very important for a large distributed system. However, the distributed, heterogeneous, and unstructured nature of the system makes this issue very challenging. The discovering mechanism has to be not only semantically rich, in order to cope with complex queries, but also scalable to handle large numbers of information sources. In this paper, we address these problems by proposing OntSum, an efficient peer-to-peer query routing scheme based on concise ontology indexing. Unlike most existing systems, our system does not assume a global ontology but heterogeneous ontologies. Peers in the system use their own ontologies to describe their resource knowledge and the network topology is adjusted according to peers' ontological properties. A novel indexing strategy enables forwarding queries only to semantically related nodes. The architecture improves interoperability among network participants and aids efficient resource discovery through an expressive query language.

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: Grid resource discovery based on semantic P2P communities
abstract: 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: 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: Mining the optimal class association rule set
abstract: We define an optimal class association rule set to be the minimum rule set with the same predictive power of the complete class association rule set. Using this rule set instead of the complete class association rule set we can avoid redundant computation that would otherwise be required for mining predictive association rules and hence improve the efficiency of the mining process significantly. We present an efficient algorithm for mining the optimal class association rule set using an upward closure property of pruning weak rules before they are actually generated. We have implemented the algorithm and our experimental results show that our algorithm generates the optimal class association rule set, whose size is smaller than 1/17 of the complete class association rule set on average, in significantly less rime than generating the complete class association rule set. Our proposed criterion has been shown very effective for pruning weak rules in dense databases.

title: Face Recognition Based on Multiple Region Features
abstract: For face recognition, face feature selection is an important step. Better features should result in better performance. This paper describes a robust face recognition algorithm using multiple face region features selected by the AdaBoost algorithm. In conventional face recognition algorithms, the face region is dealt with as a whole. In this paper we show that dividing a face into a number of sub-regions can improve face recognition performance. We use conventional AdaBoost with a weak learner based on multiple region orthogonal component principal component analysis (OCPCA) features. The regions are selected areas of the face (such as eye, mouth, nose etc.). The AdaBoost algorithm generates a strong classifier from the combination of these region features. Experiments have been done to evaluate the performance on the CMU Pose Illumination Expression (PIE) databases. Performance comparisons between single region OCPCA, our multiple region OCPCA, and published results from Visionics' FaceIt are given. Significant performance improvement is demonstrated using multiple facial region OCPCA features.

title: Observations on versioning of off-the-shelf components in industrial projects (short paper)
abstract: Using OTS (Off-The-Shelf) components in software projects has become increasing popular in the IT industry. After project managers opt for OTS components, they can decide to use COTS (Commercial-Off-The-Shelf) components or OSS (Open Source Software) components. We have done a series of interviews and surveys to document and understand industrial practice with OTS-based development in Norwegian, German, and Italian IT industry. The perspective is that of a software architect or system integrator, not a developer or maintainer of such components. The study object is a completed development project using one or several OTS components. This paper reports on the versioning aspects of OTS components in such projects. We found that one third of the COTS components actually provided source code, in addition to all OSS components. However, OTS components were seldom modified (i.e. re-used "as-is"), even if source code was available. Although backward compatibility of new releases did not cause noticeable problems for a single OTS component, using several different OTS components in a project caused difficulties in maintenance planning of asynchronous releases and system integration of new releases. Several new research questions have been formulated based on the results of this study.

title: RACCOON: a peer-based system for data integration and sharing
abstract: Recent database applications see the emerging need to support data integration in distributed, peer-to-peer environments, in which autonomous peers (sources) connected by a network are willing to exchange data and services with each other. To address related research challenges, we are developing a system called "RACCOON", which allows different sources to integrate and share their data. We use an application to show several important features of the RACCOON system. The system also suggests semantic mappings for the user to choose. We show the two different querying modes, particularly how a query is expanded using the semantic mappings in the extended querying mode to compute as many answers to the query as possible.

title: Distributed hosting of Web content with erasure coding and unequal weight assignment
abstract: By sharing and hosting personal Web content in a peer-to-peer (P2P) fashion, we may increase the bandwidth of retrieval and improve the reliability of retrieval. The cost is that the Web content has to be replicated to and stored in the peers, consuming valuable network bandwidth and peer storage space. In this work, we develop two technologies, namely hierarchical content organization with unequal weight assignment and erasure coding, to reduce the amount of content to be distributed, yet still maintain the retrieval speed up and reliability. Significant improvement over the ordinary Web server is demonstrated.