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

Erickson, A. and Stewart, I.A. and Pascual, J.A. and Navaridas, J. (2017) 'Improved routing algorithms in the dual-port datacenter networks HCN and BCN.', Future generation computer systems., 75 . pp. 58-71.

Abstract

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.

Item Type:Article
Full text:(AM) Accepted Manuscript
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1016/j.future.2017.05.004
Publisher statement:Creative Commons Attribution License (CC BY) This article is available under the terms of the Creative Commons Attribution License (CC BY). You may copy and distribute the article, create extracts, abstracts and new works from the article, alter and revise the article, text or data mine the article and otherwise reuse the article commercially (including reuse and/or resale of the article) without permission from Elsevier. You must give appropriate credit to the original work, together with a link to the formal publication through the relevant DOI and a link to the Creative Commons user license above. You must indicate if any changes are made but not in any way that suggests the licensor endorses you or your use of the work. Permission is not required for this type of reuse.
Date accepted:05 May 2017
Date deposited:12 May 2017
Date of first online publication:11 May 2017
Date first made open access:No date available

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