TY - JOUR
T1 - Dynamic walks for searching streaming media in Peer-to-Peer Networks
AU - Su, Zhou
AU - Katto, Jiro
AU - Yasuda, Yasuhiko
PY - 2004
Y1 - 2004
N2 - With the advance of network technologies, availability and popularity of streaming media contents over the P2P (Peer-to-Peer) Networks have grown rapidly in recent years. However, how to efficiently search a requested steaming media among P2P peers is still a problem which causes a serious user delay and limited hit ratio. This paper presents an efficient search method for streaming media in P2P, which reduces user response delays and exchange overhead simultaneously. Based on an analytical formulation of both streaming media and P2P peers'characteristics, we derive a search algorithm which solves the next two problems quantitatively. (1) How to decide the number of walkers (queries) at each step of search? (2) How to decide the length of walkers (queries) at each step of search? Simulation results verify that the proposed algorithm efficiently resolves the above problems and provides much better performance than conventional methods.
AB - With the advance of network technologies, availability and popularity of streaming media contents over the P2P (Peer-to-Peer) Networks have grown rapidly in recent years. However, how to efficiently search a requested steaming media among P2P peers is still a problem which causes a serious user delay and limited hit ratio. This paper presents an efficient search method for streaming media in P2P, which reduces user response delays and exchange overhead simultaneously. Based on an analytical formulation of both streaming media and P2P peers'characteristics, we derive a search algorithm which solves the next two problems quantitatively. (1) How to decide the number of walkers (queries) at each step of search? (2) How to decide the length of walkers (queries) at each step of search? Simulation results verify that the proposed algorithm efficiently resolves the above problems and provides much better performance than conventional methods.
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U2 - 10.1007/978-3-540-30541-5_19
DO - 10.1007/978-3-540-30541-5_19
M3 - Article
AN - SCOPUS:35048837122
SN - 0302-9743
VL - 3331
SP - 147
EP - 156
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -