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Improved routing algorithms in the dual-port datacenter networks HCN and BCN

Erickson, A.; Stewart, I.A.; Pascual, J.A.; Navaridas, J.

Improved routing algorithms in the dual-port datacenter networks HCN and BCN Thumbnail


A. Erickson

J.A. Pascual

J. Navaridas


We present significantly improved one-to-one routing algorithms in the datacenter networks HCN and View the MathML source in that our routing algorithms result in much shorter paths when compared with existing routing algorithms. We also present a much tighter analysis of HCN and View the MathML sourceby observing that there is a very close relationship between the datacenter networks HCN and the interconnection networks known as WK-recursive networks. We use existing results concerning WK-recursive networks to prove the optimality of our new routing algorithm for HCN and also to significantly aid the implementation of our routing algorithms in both HCN and View the MathML source. Furthermore, we empirically evaluate our new routing algorithms for View the MathML source, against existing ones, across a range of metrics relating to path-length, throughput, and latency for the traffic patterns all-to-one, bisection, butterfly, hot-region, many-all-to-all, and uniform-random, and we also study the completion times of workloads relating to MapReduce, stencil and sweep, and unstructured applications. Not only do our results significantly improve routing in our datacenter networks for all of the different scenarios considered but they also emphasise that existing theoretical research can impact upon modern computational platforms.


Erickson, A., Stewart, I., Pascual, J., & Navaridas, J. (2017). Improved routing algorithms in the dual-port datacenter networks HCN and BCN. Future Generation Computer Systems, 75, 58-71.

Journal Article Type Article
Acceptance Date May 5, 2017
Online Publication Date May 11, 2017
Publication Date May 11, 2017
Deposit Date May 11, 2017
Publicly Available Date May 12, 2017
Journal Future Generation Computer Systems
Print ISSN 0167-739X
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 75
Pages 58-71
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Accepted Journal Article (770 Kb)

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