SpiderDAN: Matching Augmentation in Demand-Aware Networks

Fuente: arXiv
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Main Authors: Figiel, Aleksander, Melnyk, Darya, Nichterlein, André, Pourdamghani, Arash, Schmid, Stefan
Format: Preprint
Published: 2024
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author Figiel, Aleksander
Melnyk, Darya
Nichterlein, André
Pourdamghani, Arash
Schmid, Stefan
author_facet Figiel, Aleksander
Melnyk, Darya
Nichterlein, André
Pourdamghani, Arash
Schmid, Stefan
contents Graph augmentation is a fundamental and well-studied problem that arises in network optimization. We consider a new variant of this model motivated by reconfigurable communication networks. In this variant, we consider a given physical network and the measured communication demands between the nodes. Our goal is to augment the given physical network with a matching, so that the shortest path lengths in the augmented network, weighted with the demands, are minimal.We prove that this problem is NP-hard, even if the physical network is a cycle. We then use results from demand-aware network design to provide a constant-factor approximation algorithm for adding a matching in case that only a few nodes in the network cause almost all the communication. For general real-world communication patterns, we design and evaluate a series of heuristics that can deal with arbitrary graphs as the underlying network structure. Our algorithms are validated experimentally using real-world traces (from e.g., Facebook) of data centers.
format Preprint
id arxiv_https___arxiv_org_abs_2411_11426
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle SpiderDAN: Matching Augmentation in Demand-Aware Networks
Figiel, Aleksander
Melnyk, Darya
Nichterlein, André
Pourdamghani, Arash
Schmid, Stefan
Data Structures and Algorithms
Networking and Internet Architecture
Graph augmentation is a fundamental and well-studied problem that arises in network optimization. We consider a new variant of this model motivated by reconfigurable communication networks. In this variant, we consider a given physical network and the measured communication demands between the nodes. Our goal is to augment the given physical network with a matching, so that the shortest path lengths in the augmented network, weighted with the demands, are minimal.We prove that this problem is NP-hard, even if the physical network is a cycle. We then use results from demand-aware network design to provide a constant-factor approximation algorithm for adding a matching in case that only a few nodes in the network cause almost all the communication. For general real-world communication patterns, we design and evaluate a series of heuristics that can deal with arbitrary graphs as the underlying network structure. Our algorithms are validated experimentally using real-world traces (from e.g., Facebook) of data centers.
title SpiderDAN: Matching Augmentation in Demand-Aware Networks
topic Data Structures and Algorithms
Networking and Internet Architecture
url https://arxiv.org/abs/2411.11426