Probability and Computing: Randomized Algorithms and Probabilistic Analysis
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
Fundamentals of wireless communication
Fundamentals of wireless communication
Efficient algorithms of video replication and placement on a cluster of streaming servers
Journal of Network and Computer Applications
On the optimization of storage capacity allocation for content distribution
Computer Networks: The International Journal of Computer and Telecommunications Networking
Greening the internet with nano data centers
Proceedings of the 5th international conference on Emerging networking experiments and technologies
Epidemics and Rumours in Complex Networks
Epidemics and Rumours in Complex Networks
Achievable catalog size in peer-to-peer video-on-demand systems
IPTPS'08 Proceedings of the 7th international conference on Peer-to-peer systems
On fairness, optimal download performance and proportional replication in peer-to-peer networks
NETWORKING'05 Proceedings of the 4th IFIP-TC6 international conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communication Systems
Minimizing delivery cost in scalable streaming content distribution systems
IEEE Transactions on Multimedia
Push-to-Peer Video-on-Demand System: Design and Evaluation
IEEE Journal on Selected Areas in Communications
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In this paper, we address the problem of content placement in peer-to-peer (P2P) systems, with the objective of maximizing the utilization of peers' uplink bandwidth resources. We consider system performance under a many-user asymptotic. We distinguish two scenarios, namely "Distributed Server Networks" (DSNs) for which requests are exogenous to the system, and "Pure P2P Networks" (PP2PNs) for which requests emanate from the peers themselves. For both scenarios, we consider a loss network model of performance and determine asymptotically optimal content placement strategies in the case of a limited content catalog. We then turn to an alternative "large catalog" scaling where the catalog size scales with the peer population. Under this scaling, we establish that storage space per peer must necessarily grow unboundedly if bandwidth utilization is to be maximized. Relating the system performance to properties of a specific random graph model, we then identify a content placement strategy and a request acceptance policy that jointly maximize bandwidth utilization, provided storage space per peer grows unboundedly, although arbitrarily slowly, with system size.