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Analysing and Leveraging Client Heterogeneity in Swarming-based Live Streaming

KhudaBukhsh, W. R. and Rueckert, J. and Wulfheide, J. and Hausheer, D. and Koeppl, H. (2016):
Analysing and Leveraging Client Heterogeneity in Swarming-based Live Streaming.
In: IFIP International Conference on Networking (NETWORKING), In: IFIP International Conference on Networking, Wien, Austria, Mai 2016, [Online-Edition: http://dl.ifip.org/db/conf/networking/networking2016/1570236...],
[Conference or Workshop Item]

Abstract

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 a pure streaming approach or in combination with tree/push mechanisms. The crucial impact of today’s variety of client systems with their heterogeneous resources is not yet well understood. In this paper, 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 contribution of this paper is, hence, twofold: (1) we develop a mathematical framework for swarming on random graphs with a focus on LDF and EDF strategies in heterogeneous scenarios; (2) we propose a mixed strategy, named SCHEDMIX, that leverages client heterogeneity. We show that SCHEDMIX outperforms LDF and EDF using different abstractions: a mean-field theoretic analysis of buffer probabilities, simulations of the stochastic model on random graphs, and a full-stack implementation of a P2P streaming system.

Item Type: Conference or Workshop Item
Erschienen: 2016
Creators: KhudaBukhsh, W. R. and Rueckert, J. and Wulfheide, J. and Hausheer, D. and Koeppl, H.
Title: Analysing and Leveraging Client Heterogeneity in Swarming-based Live Streaming
Language: English
Abstract:

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 a pure streaming approach or in combination with tree/push mechanisms. The crucial impact of today’s variety of client systems with their heterogeneous resources is not yet well understood. In this paper, 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 contribution of this paper is, hence, twofold: (1) we develop a mathematical framework for swarming on random graphs with a focus on LDF and EDF strategies in heterogeneous scenarios; (2) we propose a mixed strategy, named SCHEDMIX, that leverages client heterogeneity. We show that SCHEDMIX outperforms LDF and EDF using different abstractions: a mean-field theoretic analysis of buffer probabilities, simulations of the stochastic model on random graphs, and a full-stack implementation of a P2P streaming system.

Title of Book: IFIP International Conference on Networking (NETWORKING)
Uncontrolled Keywords: Scheduling Strategy; EDF; Scheduling Mechanism; Stochastic Model; LDF
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Bioinspired Communication Systems
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications
Event Title: IFIP International Conference on Networking
Event Location: Wien, Austria
Event Dates: Mai 2016
Date Deposited: 05 Oct 2016 07:21
Official URL: http://dl.ifip.org/db/conf/networking/networking2016/1570236...
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