Extreme flow decomposition for multi-source multicast with intra-session network coding

Network coding (NC), when combined with multipath routing, enables a linear programming (LP) formulation for a multi-source multicast with intra-session network coding (MISNC) problem. However, it is still hard to solve using conventional methods due to the enormous scale of variables or constraints...

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Veröffentlicht in:Journal of parallel and distributed computing Jg. 175; S. 80 - 91
1. Verfasser: Zhang, Jianwei
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Inc 01.05.2023
Schlagworte:
Approximation algorithm
Extreme flow
Multicast
Network coding
Online algorithm
Multicast
Network coding
Extreme flow
Online algorithm
Approximation algorithm
ISSN:0743-7315, 1096-0848
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Zusammenfassung:Network coding (NC), when combined with multipath routing, enables a linear programming (LP) formulation for a multi-source multicast with intra-session network coding (MISNC) problem. However, it is still hard to solve using conventional methods due to the enormous scale of variables or constraints. In this paper, we try to solve this problem in terms of throughput maximization from an algorithmic perspective. We propose a novel formulation based on the extreme flow decomposition technique, which facilitates the design and analysis of approximation and online algorithms. For the offline scenario, we develop a fully polynomial time approximation scheme (FPTAS) which can find a (1+ω)-approximation solution for any specified ω>0. For the online scenario, we develop an online primal-dual algorithm which proves O(1)-competitive and violates link capacities by a factor of O(log⁡m), where m is the link number. The proposed algorithms share an elegant primal-dual form and thereby have inherent advantages of simplicity, efficiency, and scalability. To better understand the proposed approach, we devise delicate numerical examples on an extended butterfly network to validate the effects of algorithmic parameters and make an interesting comparison between the offline and online cases. We also perform large-scale simulations on real networks to validate the effectiveness of the proposed FPTAS and online algorithm. •Extreme flow decomposition technique for intra-session network coding.•Offline FPTAS with provable approximation ratio.•Online primal-dual algorithm with provable competitive ratio.•Large-scale experiments using public datasets.
ISSN:0743-7315
1096-0848
DOI:10.1016/j.jpdc.2023.01.003