Multi-Path Alpha-Fair Resource Allocation at Scale in Distributed Software-Defined Networks

The performance of computer networks relies on how bandwidth is shared among different flows. Fair resource allocation is a challenging problem particularly when the flows evolve over time. To address this issue, bandwidth sharing techniques that quickly react to the traffic fluctuations are of inte...

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Vydáno v:IEEE journal on selected areas in communications Ročník 36; číslo 12; s. 2655 - 2666
Hlavní autoři: Allybokus, Zaid, Avrachenkov, Konstantin, Leguay, Jeremie, Maggi, Lorenzo
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.12.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Témata:
Algorithms
alpha-fairness
alternating direction method of multipliers
Bandwidth
Computer architecture
Computer networks
Computer Science
Distributed algorithms
distributed SDN control plane
Distributed, Parallel, and Cluster Computing
Mathematics
multi-path resource allocation
Networking and Internet Architecture
Optimization and Control
Real-time systems
Resource allocation
Resource management
Software defined networking
Software-defined networks
Switches
Variation
Distributed SDN Control Plane
Alpha-Fairness
Multi-path Resource Allocation
Software-Defined Networks
Distributed Algorithms
Alternating Direction Method of Multipliers
ISSN:0733-8716, 1558-0008
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Popis
Shrnutí:The performance of computer networks relies on how bandwidth is shared among different flows. Fair resource allocation is a challenging problem particularly when the flows evolve over time. To address this issue, bandwidth sharing techniques that quickly react to the traffic fluctuations are of interest, especially in large-scale settings with hundreds of nodes and thousands of flows. In this context, we propose a distributed algorithm based on the alternating direction method of multipliers (ADMM) that tackles the multi-path fair resource allocation problem in a distributed SDN control architecture. Our ADMM-based algorithm continuously generates a sequence of resource allocation solutions converging to the fair allocation while always remaining feasible, a property that standard primal-dual decomposition methods often lack. Thanks to the distribution of all computer intensive operations, we demonstrate that we can handle large instances at scale.
Bibliografie:ObjectType-Article-1
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ISSN:0733-8716
1558-0008
DOI:10.1109/JSAC.2018.2871293