1,315 research outputs found
On game theoretic peer selection for resilient peer-to-peer media streaming
Peer-to-peer (P2P) media streaming quickly emerges as an important application over the Internet. A plethora of approaches have been suggested and implemented to support P2P media streaming. In our study, we first classified existing approaches and studied their characteristics by looking at three important quantities: number of upstream peers (parents), number of downstream peers (children), and average number of links per peer. In existing approaches, peers are assigned with a fixed number of parents without regard to their contributions, measured by the amount of outgoing bandwidths. Obviously, this is an undesirable arrangement as it leads to highly inefficient use of the P2P links. This observation motivates us to model the peer selection process as a cooperative game among peers. This results in a novel peer selection protocol such that the number of upstream peers of a peer is related to its outgoing bandwidth. Specifically, peers with larger outgoing bandwidth are given more parents, which make them less vulnerable to peer dynamics. Simulation results show that the proposed protocol improves delivery ratio using similar number of links per peer, comparing with existing approaches under a wide range of system parameters. © 2009 IEEE.published_or_final_versio
A Comprehensive Analysis of Swarming-based Live Streaming to Leverage Client Heterogeneity
Due to missing IP multicast support on an Internet scale, over-the-top media
streams are delivered with the help of overlays as used by content delivery
networks and their peer-to-peer (P2P) extensions. In this context,
mesh/pull-based swarming plays an important role either as pure streaming
approach or in combination with tree/push mechanisms. However, the impact of
realistic client populations with heterogeneous resources is not yet fully
understood. In this technical report, we contribute to closing this gap by
mathematically analysing the most basic scheduling mechanisms latest deadline
first (LDF) and earliest deadline first (EDF) in a continuous time Markov chain
framework and combining them into a simple, yet powerful, mixed strategy to
leverage inherent differences in client resources. The main contributions are
twofold: (1) a mathematical framework for swarming on random graphs is proposed
with a focus on LDF and EDF strategies in heterogeneous scenarios; (2) a mixed
strategy, named SchedMix, is proposed that leverages peer heterogeneity. The
proposed strategy, SchedMix is shown to outperform the other two strategies
using different abstractions: a mean-field theoretic analysis of buffer
probabilities, simulations of a stochastic model on random graphs, and a
full-stack implementation of a P2P streaming system.Comment: Technical report and supplementary material to
http://ieeexplore.ieee.org/document/7497234
A new analytical framework for studying protocol diversity in P2P networks
Thanks to years of research and development, current peer-to-peer (P2P) networks are anything but a homogeneous system from a protocol perspective. Specifically, even for the same P2P system (e.g., BitTorrent), a large number of protocol variants have been designed based on game theoretic considerations with the objective to gain performance advantages. We envision that such variants could be deployed by selfish participants and interact with the original prescribed protocol as well as among them. Consequently, a meta-strategic situation - judiciously selection of different protocol variants - will emerge. In this work, we propose a general framework, Migration, based on evolutionary game theory to study the coevolution of peers for selfish protocol selection, and, most importantly, its impact on system performance. We apply Migration to P2P systems and draw on extensive simulations to characterize the dynamics of selfish protocol selection. The revealed evolution patterns shed light on both theoretical study and practical system design. © 2013 IEEE.published_or_final_versio
A credit-based approach to scalable video transmission over a peer-to-peer social network
PhDThe objective of the research work presented in this thesis is to study
scalable video transmission over peer-to-peer networks. In particular,
we analyse how a credit-based approach and exploitation of social networking
features can play a significant role in the design of such systems.
Peer-to-peer systems are nowadays a valid alternative to the traditional
client-server architecture for the distribution of multimedia content, as
they transfer the workload from the service provider to the final user,
with a subsequent reduction of management costs for the former. On
the other hand, scalable video coding helps in dealing with network
heterogeneity, since the content can be tailored to the characteristics
or resources of the peers. First of all, we present a study that evaluates
subjective video quality perceived by the final user under different
transmission scenarios. We also propose a video chunk selection algorithm
that maximises received video quality under different network
conditions. Furthermore, challenges in building reliable peer-to-peer
systems for multimedia streaming include optimisation of resource allocation
and design mechanisms based on rewards and punishments that
provide incentives for users to share their own resources. Our solution
relies on a credit-based architecture, where peers do not interact with
users that have proven to be malicious in the past. Finally, if peers
are allowed to build a social network of trusted users, they can share
the local information they have about the network and have a more
complete understanding of the type of users they are interacting with.
Therefore, in addition to a local credit, a social credit or social reputation
is introduced. This thesis concludes with an overview of future
developments of this research work
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