Location-Aware Optimal Resource Selection Method for P2P-Based Contents Management and Real-Time Distribution

Hiroshi YAMAMOTO  Katsuyuki YAMAZAKI  

IEICE TRANSACTIONS on Information and Systems   Vol.E96-D   No.2   pp.213-225
Publication Date: 2013/02/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E96.D.213
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Section on The Internet Architectures, Protocols, and Applications for Diversified Futures)
peer-to-peer,  content distribution,  DHT,  location-aware node selection,  network coordinate,  

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With the wide-spread use of high-speed network connections and high performance mobile/sensor terminals available, new interactive services based on real-time contents have become available over the Internet. In these services, end-nodes (e.g, smart phone, sensors), which are dispersed over the Internet, generates the real-time contents (e.g, live video, sensor data about human activity), and those contents are utilized to support many kinds of human activities seen in the real world. For the services, a new decentralized contents distribution system which can accommodate a large number of content distributions and which can minimize the end-to-end streaming delay between the content publisher and the subscribers is proposed. In order to satisfy the requirements, the proposed content distribution system is equipped with utilizing two distributed resource selection methods. The first method, distributed hash table (DHT)-based contents management, makes it possible for the system to efficiently decide and locate the server managing content distributions in completely decentralized manner. And, the second one, location-aware server selection, is utilized to quickly select the appropriate servers that distribute the streamed contents to all subscribers in real time. This paper considers the performance of the proposed resource selection methods using a realistic computer simulation and shows that the system with the proposed methods has scalability for a large-scale distributed system that attracts a very large number of users, and achieves real-time locating of the contents without degrading end-to-end streaming delay of content.