Matin: a random network coding based framework for high quality peer-to-peer live video streaming
Behrang Barekatain,Dariush Khezrimotlagh,Mohd Aizaini Maarof,Hamid Reza Ghaeini,Shaharuddin Salleh,Alfonso Ariza Quintana,Behzad Akbari,Alicia Triviño Cabrera +7 more
TL;DR: The results obtained from simulation using OMNET++ show that the MATIN substantially outperforms the RNC which uses the Gauss-Jordan elimination method by providing better video quality on peers in terms of the four important performance metrics including video distortion, dependency distortion, End-to-End delay and Initial Startup delay.
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Abstract: In recent years, Random Network Coding (RNC) has emerged as a promising solution for efficient Peer-to-Peer (P2P) video multicasting over the Internet This probably refers to this fact that RNC noticeably increases the error resiliency and throughput of the network However, high transmission overhead arising from sending large coefficients vector as header has been the most important challenge of the RNC Moreover, due to employing the Gauss-Jordan elimination method, considerable computational complexity can be imposed on peers in decoding the encoded blocks and checking linear dependency among the coefficients vectors In order to address these challenges, this study introduces MATIN which is a random network coding based framework for efficient P2P video streaming The MATIN includes a novel coefficients matrix generation method so that there is no linear dependency in the generated coefficients matrix Using the proposed framework, each peer encapsulates one instead of n coefficients entries into the generated encoded packet which results in very low transmission overhead It is also possible to obtain the inverted coefficients matrix using a bit number of simple arithmetic operations In this regard, peers sustain very low computational complexities As a result, the MATIN permits random network coding to be more efficient in P2P video streaming systems The results obtained from simulation using OMNET++ show that it substantially outperforms the RNC which uses the Gauss-Jordan elimination method by providing better video quality on peers in terms of the four important performance metrics including video distortion, dependency distortion, End-to-End delay and Initial Startup delay
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Citations
TIHOO: An Enhanced Hybrid Routing Protocol in Vehicular Ad-hoc Networks
TL;DR: TIHOO, an enhanced intelligent hybrid routing protocol based on improved fuzzy and cuckoo approaches to find the most stable path between a source and a destination node, considerably improves network throughput, routing overhead, packet delivery ratio, packet loss ratio, and end-to-end delay compared to similar routing protocols.
Efficient P2P Live Video Streaming Over Hybrid WMNs Using Random Network Coding
Behrang Barekatain,Dariush Khezrimotlagh,Mohd Aizaini Maarof,Hamid Reza Ghaeini,Alfonso Ariza Quintana,Alicia Triviño Cabrera +5 more
TL;DR: Simulation results in the OMNeT++ framework depict that the applied method provides high video quality on the nodes by addressing the mentioned challenges, even if high mobility rates exist in the WMN.
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Peer-to-Peer Live Video Streaming with Rateless Codes for Massively Multiplayer Online Games
Shakeel Ahmad,Christos Bouras,Eliya Buyukkaya,Muneeb Dawood,Raouf Hamzaoui,Vaggelis Kapoulas,Andreas Papazois,Gwendal Simon +7 more
TL;DR: A multi-level multi-overlay hybrid peer-to-peer live video system that enables players of Massively Multiplayer Online Games to simultaneously stream the video of their game and watch the game videos of other players.
GAZELLE: An Enhanced Random Network Coding Based Framework for Efficient P2P Live Video Streaming Over Hybrid WMNs
Behrang Barekatain,Dariush Khezrimotlagh,Mohd Aizaini Maarof,Alfonso Ariza Quintana,Alicia Triviño Cabrera +4 more
TL;DR: GAZELLE not only decreases the imposed computational complexity and transmission overhead due to using RNC considerably, but it also efficiently routes video packets through those gadgets which does not require neither high battery energy sources nor high CPU power.
11
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