The cost of recovery protocols in web-based database systems

The cost of recovery protocols is important with respect to system performance during normal operation and failure in terms of overhead, and time taken to recover failed transactions. The cost of recovery protocols for web database systems has not been addressed much. In this paper, we present a quantitative study of cost of recovery protocols. For this purpose, we use an experiment setup to evaluate the performance of two recovery algorithms, namely the, two-phase commit algorithm and log-based algorithm. Our work is a step towards building reliable protocols for web database systems.

Analyzing inconsistency toward enhancing integration of biological molecular databases

The rapid growth of biological databases not only provides biologists with abundant data but also presents a big challenge in relation to the analysis of data. Many data analysis approaches such as data mining, information retrieval and machine learning have been used to extract frequent patterns from diverse biological databases. However, the discrepancies, due to the differences in the structure of databases and their terminologies, result in a significant lack of interoperability. Although ontology-based approaches have been used to integrate biological databases, the inconsistent analysis of biological databases has been greatly disregarded. This paper presents a method by which to measure the degree of inconsistency between biological databases. It not only presents a guideline for correct and efficient database integration, but also exposes high quality data for data mining and knowledge discovery.

Web communities analysis and construction

Yanchun Zhang and his co-authors explain how to construct and analyse Web communities based on information like Web document contents, hyperlinks, or user access logs. Their approaches combine results from Web search algorithms, Web clustering methods, and Web usage mining. They also detail the necessary preliminaries needed to understand the algorithms presented, and they discuss several successful existing applications. Researchers and students in information retrieval and Web search find in this all the necessary basics and methods to create and understand Web communities. Professionals developing Web applications will additionally benefit from the samples presented for their own designs and implementations

Intelligent financial news digest system

We present an agent-based system Intelligent Financial News Digest System (IFNDS) for analyzing online financial news articles and associated material. The system can abstract, synthesize, digest, and classify the contents, and assesses whether the report is favorable to any company discussed in the reports. It integrates artificial intelligence technologies including traditional information retrieval and extraction techniques for the news analysis. It makes use of keyword statistics and backpropagation training data to identify companies named in reportage whether it is, evaluatively speaking, positive, negative or neutral. The system would be of use to media such as clipping services, media management, advertising, public relations, public interest, and e-commerce professionals and government non-governmental bodies interested in monitoring the media profiles of corporations, products, and issues.

Spectral kernels for classification

Spectral methods, as an unsupervised technique, have been used with success in data mining such as LSI in information retrieval, HITS and PageRank in Web search engines, and spectral clustering in machine learning. The essence of success in these applications is the spectral information that captures the semantics inherent in the large amount of data required during unsupervised learning. In this paper, we ask if spectral methods can also be used in supervised learning, e.g., classification. In an attempt to answer this question, our research reveals a novel kernel in which spectral clustering information can be easily exploited and extended to new incoming data during classification tasks. From our experimental results, the proposed Spectral Kernel has proved to speedup classification tasks without compromising accuracy.

Discovering Web Page Communities

The rapid development of Web technologies has made the World Wide Web a huge information source. However, due to the lack of a well-defined underlying data model for Web documents, effectively and efficiently finding required information and managing Web data are usually tedious and difficult tasks when using conventional information retrieval and data management techniques. The Web page community, defined as a set of Web-based documents with its own logical and/or semantic structures, provides a flexible and effective approach to support Wed data management, information retrieval and applications. This book addresses using hyperlink information to discover Web page communities. The work establishes a uniform framework for hyperlink analysis and community construction. Algorithms, supporting mechanisms and data models are proposed in the book. This book should help shed some light on this new and exciting research and application area. It is useful to researchers and students in Web mining, Web data management and information retrieval, as well as to professionals who may be considering utilizing Web communities to improve their applications.

The small rural school principalship : key challenges and cross-school responses

This article explores the responses of school principals of small rural schools in Victoria, Australia to leadership challenges they identify as characteristic of these contexts. The research is an exercise in grounded theory building, with the focus on the principalship as it is enacted in small rural settings. The article also seeks to trace the impact of macro and meso influences on micro rural contexts. While many very positive attributes of small rural schools are evident, this article speaks to principalship engagement with contextual problems – issues concerning work intensification, role multiplicity, school viability, new regulatory funding requirements and the abandonment of equity policies in education – since there is a dearth of information in Australia at this time about how school principals confront these challenges in small rural locations. The research exposes a growing culture of creative collaborative responses to the pervasive impediments of leading small rural schools.

Source-based filtering scheme against DDOS attacks

IP address spoofing is employed by a lot of DDoS attack tools. Most of the current research on DDoS attack packet filtering depends on cooperation among routers, which is hard to achieve in real campaigns. Therefore, in the paper, we propose a novel filtering scheme based on source information in this paper to defend against various source IP address spoofing. The proposed method works independently at the potential victim side, and accumulates the source information of its clients, for instance, source IP addresses, hops from the server during attacks free period. When a DDoS attack alarm is raised, we can filter out the attack packets based on the accumulated knowledge of the legitimate clients. We divide the source IP addresses into n(1 ≤ n ≤ 32) segments in our proposed algorithm; as a result, we can therefore release the challenge storage and speed up the procedure of information retrieval. The system which is proposed by us and the experiments indicated that the proposed method works effectively and efficiently.

Reducing cache lookup and publish overhead through locality awareness in P2P web caching

Peer-to-Peer (P2P) Web caching has been a hot research topic in recent years as it can create scalable and robust designs for decentralized Internet-scale applications. However, many P2P Web caching systems suffer expensive overheads such as lookup and publish messages, and lack of locality awareness. In this paper we present the development of a locality aware P2P cache system to overcome these limitations by using routing table locality, aggregation and soft state. The experiments show that our P2P cache system improves the performance of index operations through the reduction of the amount of information processed by nodes, the reduction of the number of index messages sent by nodes, and the improvement of the locality of cache pointers.

Anycast services and its applications

Anycast in next generation Internet Protocol is a hot topic in the research of computer networks. It has promising potentials and also many challenges, such as architecture, routing, Quality-of-Service, anycast in ad hoc networks, application-layer anycast, etc. In this thesis, we tackle some important topics among them. The thesis at first presents an introduction about anycast, followed by the related work. Then, as our major contributions, a number of challenging issues are addressed in the following chapters. We tackled the anycast routing problem by proposing a requirement based probing algorithm at application layer for anycast routing. Compared with the existing periodical based probing routing algorithm, the proposed routing algorithm improves the performance in terms of delay. We addressed the reliable service problem by the design of a twin server model for the anycast servers, providing a transparent and reliable service for all anycast queries. We addressed the load balance problem of anycast servers by proposing new job deviation strategies, to provide a similar Quality-of-Service to all clients of anycast servers. We applied the mesh routing methodology in the anycast routing in ad hoc networking environment, which provides a reliable routing service and uses much less network resources. We combined the anycast protocol and the multicast protocol to provide a bidirectional service, and applied the service to Web-based database applications, achieving a better query efficiency and data synchronization. Finally, we proposed a new Internet based service, minicast, as the combination of the anycast and multicast protocols. Such a service has potential applications in information retrieval, parallel computing, cache queries, etc. We show that the minicast service consumes less network resources while providing the same services. The last chapter of the thesis presents the conclusions and discusses the future work.

Evaluation of Australian undergraduate engineering management education for flexible delivery

This thesis examines issues in Australian undergraduate engineering management studies in the context of flexible learning delivery. It is proposed that, within an Australian context: a) the management skills and competencies required by graduate engineers can be determined and classified on a rational basis, permitting an educational focus on those elements most appropriate for graduates; and b) on-line and other computer-based technologies are a practical and effective method for the support of undergraduate engineering management studies. The doctoral project incorporates: • an examination of the nature of engineering management; • a review of the relevant literature establishing the importance of management studies in undergraduate engineering courses; • a review of historical and recent developments in Australian undergraduate engineering management studies; • an investigation of the management skills and competencies required by graduate engineers - based on original research; • an examination of flexible delivery of engineering education - based on professional practice experience; and • an evaluation of case studies of flexible delivery of engineering management education - based on original research and professional practice experience. A framework of ranked classified management skills is developed. Broadly, the ranking framework is generic professional skills, followed by general management skills and technical discipline specific management skills, followed by other professional discipline skills and theoretical skills. This framework provides a rational basis for design of undergraduate engineering management studies. This is supplemented by consideration of the management skills required for the future of engineering practice. It is concluded that undergraduate engineering management education is well suited to delivery and support by on-line and computer-based technology. Recent developments in improved access to the Internet, software systems for on-line collaboration and changes in copyright legislation to create a broad-based right to communication via on-line media have contributed to the facilitation of on-line delivery of teaching and learning. It is noted that though many on-line infrastructure issues have been satisfactorily resolved, higher level issues will emerge as being crucial, including the academic staff development and reward for operating in an online teaching environment and the financial sustainability of on-line development and delivery of courses.

Seeing the light : diet related variation in the vision of Platycercus elegans

 Poster Presentation

A locality aware cache diffusion system

Web caching is a widely deployed technique to reduce the load to web servers and to reduce the latency for web browsers. Peer-to-Peer (P2P) web caching has been a hot research topic in recent years as it can create scalable and robust designs for decentralized internet-scale applications. However, many P2P web caching systems suffer expensive overheads such as lookup and publish messages, and lack locality awareness. In this paper, we present the development of a locality aware cache diffusion system that makes use of routing table locality, aggregation, and soft state to overcome these limitations. The analysis and experiments show that our cache diffusion system reduces the amount of information processed by nodes, reduces the number of index messages sent by nodes, and improves the locality of cache pointers.