Guihai Chen – författare

Welcome to the proceedings of the ISPA 2005 workshops, held in the city of Nanjing, China. For the first time eight workshops were held in conjunction with the 3rd International Symposium on Parallel and Distributed Processing and Applications (ISPA 2005), to encourage interaction between researchers and practitioners. Workshop topics are, of course, in line with the conference's scientific scope and the workshops provided a forum for groups of researchers and practitioners to meet together more closely, to exchange opinions and advanced ideas, and to share preliminary results on focused issues in an atmosphere that fostered interaction and problem solving.The conference hosted eight half-day workshops: The International Workshop on Applications and Economics of Peer-to-Peer Systems organized by Qianni Deng and Zhichen Xu; the International Workshop on Advanced Storage Technology and Autonomic Distributed Data organized by Jiwu Shu and Weimin Zheng; the International Workshop on Bioinformatics organized by Mathew Palaka, Jake Chen and Zongben Xu; the International Workshop on Grid Computing in China organized by Hai Jin and Minglu Li; the International Workshop on Information Assurance in Distributed Systems organized by Peng Liu and Meng Yu; the International Workshop on Mobile Ad-hoc and Ubiquitous Sensor Networks organized by Anu Bourgeois and Wei Lou; the International Workshop on Service Grid Computing and Applications organized by Nong Xiao and Yunhao Liu; and the International Workshop on Web Information Systems and Applications organized by Baowen Xu.

This book investigates the cloud-based techniques of content distribution mainly for mobile Internet. Lastly, it includes an educational and experimental cloud computing platform allowing public access, which benefits researchers, practitioners, and developers in the field of cloud computing/storage and mobile Internet.

This book provides a comprehensive introduction to applying compressive sensing to improve data quality in the context of mobile crowdsensing. It addresses the following main topics: recovering missing data, efficiently collecting data, preserving user privacy, and detecting false data.Mobile crowdsensing, as an emerging sensing paradigm, enables the masses to take part in data collection tasks with the aid of powerful mobile devices. However, mobile crowdsensing platforms have yet to be widely adopted in practice, the major concern being the quality of the data collected. There are numerous causes: some locations may generate redundant data, while others may not be covered at all, since the participants are rarely systematically coordinated; privacy is a concern for some people, who don’t wish to share their real-time locations, and therefore some key information may be missing; further, some participants may upload fake data in order to fraudulently gain rewards. Toaddress these problematic aspects, compressive sensing, which works by accurately recovering a sparse signal using very few samples, has proven to offer an effective solution.

It addresses the following main topics: recovering missing data, efficiently collecting data, preserving user privacy, and detecting false data.Mobile crowdsensing, as an emerging sensing paradigm, enables the masses to take part in data collection tasks with the aid of powerful mobile devices.

Content distribution, i.e., distributing digital content from one node to another node or multiple nodes, is the most fundamental function of the Internet.

Content distribution, i.e., distributing digital content from one node to another node or multiple nodes, is the most fundamental function of the Internet.