Distributed hosting of Web content with erasure coding and unequal weight assignment
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.

title: Compression of the layered depth image
abstract: A layered depth image (LDI) is a new popular representation and rendering method for objects with complex geometries. Similar to a 2D image, the LDI consists of an array of pixels. However, unlike the 2D image, an LDI pixel has depth information, and there are multiple layers at a pixel location. In this paper, we develop a novel LDI compression algorithm that handles the multiple layers and the depth coding. The algorithm records the number of LDI layers at each pixel location, and compresses LDI color and depth components separately. For LDI layer with sparse pixels, the data is aggregated and then encoded. An empirical rate-distortion model is used to optimally allocate bits among different components. Compared with benchmark compression tools such as JPEG-2000 and MPEG-4, our scheme improves the compression performance significantly.

title: Crossing Boundaries with Web-Based Tools for Learning Object Evaluation
abstract: Learning object repositories and evaluation tools have the potential to serve as sites for interaction among different cultures and communities of practice. This paper outlines the web-based learning object evaluation tools we have developed, describes our current efforts to extend those tools to a wider range of user communities, and considers methods for fostering interaction among user communities. The approaches considered include establishing shared but differentiated learning object evaluation standards, mapping between local languages, ontologies and practices, and recommending objects across community boundaries.

title: A semantics-based routing scheme for grid resource discovery
abstract: Grid technologies enable the sharing of a wide variety of distributed resources. To fully utilize these resources, effective resource discovery mechanisms are necessities. However, the complicated and dynamic characteristics of grid resources make sharing and discovering them a challenging issue. In this paper, we propose a peer-to-peer (P2P) based overlay network to assist the efficient resource discovery and query. The framework is based on the RDF metadata infrastructure, allowing a rich and extensible description of resources. To avoid flooding the network with a query, we propose a comprehensive semantics-based query forwarding strategy, which only forwards queries to semantically related nodes. After the related nodes have been located, the original RDF query is used to do the final query and retrieval. Results from simulation experiments demonstrate that this architecture is scalable and efficient

title: Bioinformatics Web Services
abstract: Web services is distributed computing technology that provides software services over the Web. The Cyberinfrastructure Group at the Virginia Bioinformatics Institute (VBI) has adopted the Web service architecture and wrapped a wide variety of bioinformatics applications and data resources using the technology. Users can browse various data resources and invoke analysis tools through the services deployed at VBI. We have also developed an integrated client environment, ToolBus, which is available from http://pathport.vbi.vt.edu/download. A use case is given to demonstrate the use of Web services through ToolBus. A complete list of Web services is included.

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: Joint image compression and classification with vector quantization and a two dimensional hidden Markov model
abstract: We present an algorithm to achieve good compression and classification for images using vector quantization and a two dimensional hidden Markov model. The feature vectors of image blocks are assumed to be generated by a two dimensional hidden Markov model. We first estimate the parameters of the model, then design a vector quantizer to minimize a weighted sum of compression distortion and classification risk, the latter being defined as the negative of the maximum log likelihood of states and feature vectors. The algorithm is tested on both synthetic data and real image data. The extension to joint progressive compression and classification is discussed.