Optimizing Data Center Network Performance: A Comprehensive Analysis of Speed Testing, Caching, and Network Coding in Software Defined Networking

This study explores the application of Software Defined Networking (SDN) to optimize data center network performance by employing a series of innovative techniques tested within a Mininet-emulated dumbbell network topology. We precisely assess network behavior under different protocols and configurations, including IPerf3 in both Cubic and Bottleneck Bandwidth and Round-trip propagation time (BBR) modes, as well as UDPST (User Datagram Protocol Speed Test). Results highlight IPerf3 in BBR mode as superior in stability and performance. Additionally, we investigate various caching architectures—singular, split, and multi-cache—with multi-cache configurations demonstrating the best performance in terms of capacity and access time. Furthermore, network coding strategies like XOR coding and Random Packet Spraying (RPS) are analyzed for their effectiveness in reducing packet loss and retransmissions, with RPS showing a notable decrease in retransmission rates. Collectively, these insights contribute significantly to SDN implementations aimed at enhancing the operational efficiency of data centers.

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Publication Details

Published
2024-10-28
DOI
https://doi.org/10.23919/cnsm62983.2024.10814598
Citations
1
Primary Topic
Software-Defined Networks and 5G
Type
article
Field-Weighted Citation Impact
0.35
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Optimizing Data Center Network Performance: A Comprehensive Analysis of Speed Testing, Caching, and Network Coding in Software Defined Networking

Aaron Lee, Souryendu Das, James S. Adamson, Stavros Kalafatis et al.
1 citations
Software-Defined Networks and 5G
0.35
article

Optimizing Data Center Network Performance: A Comprehensive Analysis of Speed Testing, Caching, and Network Coding in Software Defined Networking

Aaron Lee, Souryendu Das, James S. Adamson, Stavros Kalafatis, Vedant Vaideswar
article en
1 citations

Abstract

This study explores the application of Software Defined Networking (SDN) to optimize data center network performance by employing a series of innovative techniques tested within a Mininet-emulated dumbbell network topology. We precisely assess network behavior under different protocols and configurations, including IPerf3 in both Cubic and Bottleneck Bandwidth and Round-trip propagation time (BBR) modes, as well as UDPST (User Datagram Protocol Speed Test). Results highlight IPerf3 in BBR mode as superior in stability and performance. Additionally, we investigate various caching architectures—singular, split, and multi-cache—with multi-cache configurations demonstrating the best performance in terms of capacity and access time. Furthermore, network coding strategies like XOR coding and Random Packet Spraying (RPS) are analyzed for their effectiveness in reducing packet loss and retransmissions, with RPS showing a notable decrease in retransmission rates. Collectively, these insights contribute significantly to SDN implementations aimed at enhancing the operational efficiency of data centers.

Texas A&M University (US)
Openalex Percentile: Top 35%
Software-Defined Networks and 5G
0.35
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Optimizing Data Center Network Performance: A Comprehensive Analysis of Speed Testing, Caching, and Network Coding in Software Defined Networking — Aaron Lee, Souryendu Das, et al. · (2024) | TGRS Research Map | TGRS