Authors:
Pablo Romero
;
María Elisa Bertinat
;
Darío Padula
;
Pablo Rodríguez-Bocca
and
Franco Robledo Amoza
Affiliation:
Universidad de la República, Uruguay
Keyword(s):
Peer-to-peer, Piece selection strategies, Bandwidth, Free-riding.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Applications
;
Artificial Intelligence
;
Bioinformatics
;
Biomedical Engineering
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Mathematical Modeling
;
Methodologies and Technologies
;
Network Optimization
;
Operational Research
;
Optimization
;
OR in Telecommunications
;
Pattern Recognition
;
Simulation
;
Software Engineering
;
Symbolic Systems
Abstract:
Peer-to-peer networks are strongly based on cooperation. The users, called peers, communicate basically in
a three-level based policy. In the first one, peers discover others interested in the same content, and is called
swarm selection strategy (or swarming). Then, peers must select the best ones to cooperate, what is called
peer selection strategy. Finally, peers cooperate sending pieces to each other, and the planning must attend the
piece selection strategy.
In this paper we propose an extension of a simple model based on cooperation for peer-to-peer video streaming
networks. We assume that the swarming classifies peers according to their bandwidth. In this model we meet
both the peer and the piece selection strategies, for simplified scenarios. The aim is to design network policies
in order to achieve the highest continuity of video reproduction when peers reach a stationary state. We show
that under full knowledge, the network can scale even under free-riding effects. At the sa
me time, we provide
theoretical results that reveal Rarest First has a poor performance in comparison with other techniques. Finally,
we analyze the scalability in a worst-case scenario when a variable amount of special peers are included in the
network.
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