DDLS : extending open hypermedia systems into peer-to-peer environments

FACULTY OF ENGINEERING AND APPLIED SCIENCE SCHOOL OF ELECTRONICS AND COMPUTER SCIENCE Doctor of Philosophy DDLS: EXTENDING OPEN HYPERMEDIA SYSTEMS INTO PEER-TO-PEER ENVIRONMENTS by Jing Zhou Peer-to-peer (P2P) computing is primarily characterised by decentralisation, scalability, anonymity, self-organisation and ad hoc connectivity. It attracted considerable attention in open hypermedia research due to its potential for supporting collaboration among a community of people sharing similar knowledge background. The aim of this research is to investigate the feasibility and potential benefits of incorporating the P2P paradigm in open hypermedia systems to support resource sharing-based collaboration. This is accomplished by utilising a distributed dynamic link service (DDLS) as a test bed, addressing issues that arise from implementing the paradigm, and demonstrating the efficiency of proposed techniques through simulation. This research begins with the development of a prototype DDLS using the open hypermedia paradigm for storing and presenting resources and a centralised P2P model which adopts a central service directory for publishing and discovering resources in a well-arranged environment. This is enhanced by an operational analysis and feature comparison between prototypes based on the traditional client-server and the centralised P2P models. Various P2P models are analysed to identify the key characteristics of and requirements for the DDLS using an unstructured P2P model which empowers collaboration in an ad hoc environment. The second phase of this research concentrates on overcoming the challenges of resource description, publishing and discovery posed by the unstructured P2P DDLS: using RDF to encode information about resources, developing a clustering technique to group resources and form the information space; and creating a semantic search mechanism to discover resources; respectively. Finally, this research proposes re-organisation techniques based on the exponential decay function and the naive estimator to enhance the performance of resource discovery in resource sharing-based collaboration.