Resource discovery in unstructured peer-to-peer (P2P) networks is important in the field of grid computing. Breadth-first search (BFS) is widely used for resource discovery in unstructured P2P networks. The technique is proven to return as many search results as possible. However, the network cost of the technique is high due to the flooding of query messages that can degenerate the performance of the whole network. The objective of this study is to optimise the BFS technique, so that it will produce good search results without flooding the network with unnecessary walkers. Several resource discovery techniques used in unstructured P2P networks are discussed and categorised. P2P simulators that are used for P2P network experiments were studied in accordance with their characteristics such as, scalability, extensibility and support status. Several network topology generators were also scrutinised and selected in order to find out the most real-life like network generation model for unstructured P2P experiments. Multiple combinations of five-tuple alpha multipliers have been experimented to find out the best set to make-BFS. In our test, the-BFS increases the query efficiency of the conventional BFS from 55.67% to 63.15%.
The number of research papers on Motion Capture technologies published in conferences and journals has been rapidly increasing due to the emerging of new technologies, software and hardware which create new challenges and opportunities for Martial Arts research. Current trend of the Martial Arts using Motion Capture technologies (MAMoCap) researches consists of phases of MoCap-Processing and Post-MoCap-Processing; contexts of algorithms, performance and system development; and feedbacks of intrinsic and extrinsic. The purpose of this paper is to study and explore the potential future trend of research and publications pertaining to MAMoCap researches. A systematic survey of research publications was conducted through the topic of Martial Art (MA) and Motion Capture (MoCap) in order to retrieve the scientific articles published in FOUR (4) established publishers including SPRINGERLINK, SCIENCEDIRECT, IEEE and ACM. Search refinements were done by the inclusions criteria of document types of academic journals and conference proceedings; and by the exceptions criteria of letters, editorials and book reviews. The findings show that only 27% of the publications have been selected while other 73% have been classified as irrelevant contents due to none significance and relevance to the MAMoCap researches. Analysis on the research phases, contexts and feedbacks has been conducted and discussed in detailed for pertaining knowledge gaps and future research agenda. Based on the preliminary study, a framework of EFs-Based Automated Evaluation System for the martial arts should be proposed.
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