The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Daya tampung rangkaian telah menjadi isu penting untuk analisis data besar pada sistem Pengkomputeran Skala Gudang (WSC). Telah dilaporkan bahawa rangkaian antara suis yang disambungkan secara rawak boleh membesarkan daya pemprosesan rangkaian. Untuk rangkaian tidak teratur, kaedah penghalaan berbilang laluan dipanggil k-penghalaan laluan terpendek digunakan secara konvensional. Walau bagaimanapun, ia tidak boleh mengeksploitasi laluan yang lebih panjang daripada terpendek dengan cekap yang akan menjadi laluan lencongan untuk mengelakkan kesesakan. Dalam karya ini, kaedah penghalaan novel dipanggil k-penghalaan laluan yang dioptimumkan untuk mencapai daya pemprosesan yang tinggi dicadangkan untuk rangkaian yang tidak teratur. Kami memperkenalkan heuristik untuk memilih laluan lencongan yang boleh mengelakkan kesesakan dalam rangkaian untuk meningkatkan daya pemprosesan rangkaian kes purata. Keputusan eksperimen oleh simulasi rangkaian menunjukkan bahawa cadangan k- penghalaan laluan yang dioptimumkan boleh meningkatkan daya pemprosesan ketepuan sehingga 18.2% berbanding dengan konvensional k-laluan laluan terpendek. Selain itu, ia boleh mengurangkan masa pengiraan yang diperlukan untuk pengoptimuman kepada 1/2760 pada tahap minimum berbanding kaedah kami yang dicadangkan sebelum ini.
Ryuta KAWANO
Japan Advanced Institute of Science and Technology
Ryota YASUDO
Hiroshima University
Hiroki MATSUTANI
Keio University
Michihiro KOIBUCHI
National Institute of Informatics
Hideharu AMANO
Keio University
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Salinan
Ryuta KAWANO, Ryota YASUDO, Hiroki MATSUTANI, Michihiro KOIBUCHI, Hideharu AMANO, "Traffic-Independent Multi-Path Routing for High-Throughput Data Center Networks" in IEICE TRANSACTIONS on Information,
vol. E103-D, no. 12, pp. 2471-2479, December 2020, doi: 10.1587/transinf.2020PAP0005.
Abstract: Network throughput has become an important issue for big-data analysis on Warehouse-Scale Computing (WSC) systems. It has been reported that randomly-connected inter-switch networks can enlarge the network throughput. For irregular networks, a multi-path routing method called k-shortest path routing is conventionally utilized. However, it cannot efficiently exploit longer-than-shortest paths that would be detour paths to avoid bottlenecks. In this work, a novel routing method called k-optimized path routing to achieve high throughput is proposed for irregular networks. We introduce a heuristic to select detour paths that can avoid bottlenecks in the network to improve the average-case network throughput. Experimental results by network simulation show that the proposed k-optimized path routing can improve the saturation throughput by up to 18.2% compared to the conventional k-shortest path routing. Moreover, it can reduce the computation time required for optimization to 1/2760 at a minimum compared to our previously proposed method.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2020PAP0005/_p
Salinan
@ARTICLE{e103-d_12_2471,
author={Ryuta KAWANO, Ryota YASUDO, Hiroki MATSUTANI, Michihiro KOIBUCHI, Hideharu AMANO, },
journal={IEICE TRANSACTIONS on Information},
title={Traffic-Independent Multi-Path Routing for High-Throughput Data Center Networks},
year={2020},
volume={E103-D},
number={12},
pages={2471-2479},
abstract={Network throughput has become an important issue for big-data analysis on Warehouse-Scale Computing (WSC) systems. It has been reported that randomly-connected inter-switch networks can enlarge the network throughput. For irregular networks, a multi-path routing method called k-shortest path routing is conventionally utilized. However, it cannot efficiently exploit longer-than-shortest paths that would be detour paths to avoid bottlenecks. In this work, a novel routing method called k-optimized path routing to achieve high throughput is proposed for irregular networks. We introduce a heuristic to select detour paths that can avoid bottlenecks in the network to improve the average-case network throughput. Experimental results by network simulation show that the proposed k-optimized path routing can improve the saturation throughput by up to 18.2% compared to the conventional k-shortest path routing. Moreover, it can reduce the computation time required for optimization to 1/2760 at a minimum compared to our previously proposed method.},
keywords={},
doi={10.1587/transinf.2020PAP0005},
ISSN={1745-1361},
month={December},}
Salinan
TY - JOUR
TI - Traffic-Independent Multi-Path Routing for High-Throughput Data Center Networks
T2 - IEICE TRANSACTIONS on Information
SP - 2471
EP - 2479
AU - Ryuta KAWANO
AU - Ryota YASUDO
AU - Hiroki MATSUTANI
AU - Michihiro KOIBUCHI
AU - Hideharu AMANO
PY - 2020
DO - 10.1587/transinf.2020PAP0005
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E103-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2020
AB - Network throughput has become an important issue for big-data analysis on Warehouse-Scale Computing (WSC) systems. It has been reported that randomly-connected inter-switch networks can enlarge the network throughput. For irregular networks, a multi-path routing method called k-shortest path routing is conventionally utilized. However, it cannot efficiently exploit longer-than-shortest paths that would be detour paths to avoid bottlenecks. In this work, a novel routing method called k-optimized path routing to achieve high throughput is proposed for irregular networks. We introduce a heuristic to select detour paths that can avoid bottlenecks in the network to improve the average-case network throughput. Experimental results by network simulation show that the proposed k-optimized path routing can improve the saturation throughput by up to 18.2% compared to the conventional k-shortest path routing. Moreover, it can reduce the computation time required for optimization to 1/2760 at a minimum compared to our previously proposed method.
ER -