Demand-Aware Network Design With Minimal Congestion and Route Lengths

Chen Avin, Kaushik Mondal, Stefan Schmid

Research output: Contribution to journalArticlepeer-review

Abstract

Emerging communication technologies allow to reconfigure the physical network topology at runtime, enabling demand-aware networks (DANs): networks whose topology is optimized toward the workload they serve. However, today, only little is known about the fundamental algorithmic problems underlying the design of such demand-aware networks. This paper presents the first bounded-degree, demand-aware network, cl-DAN, which minimizes both congestion and route lengths. The degree bound Δ is given as part of the input. The designed network is provably (asymptotically) optimal in each dimension individually: we show that there do not exist any bounded-degree networks providing shorter routes (independently of the load), nor do there exist networks providing lower loads (independently of the route lengths). The main building block of the designed cl-DAN networks are ego-trees: communication sources arrange their communication partners in an optimal tree, individually. While the union of these ego-trees forms the basic structure of cl-DANs, further techniques are presented to ensure bounded degrees (for scalability).

Original languageEnglish
JournalIEEE/ACM Transactions on Networking
DOIs
StateAccepted/In press - 1 Jan 2022

Keywords

  • approximation algorithms
  • Data centers
  • Entropy
  • IEEE transactions
  • load
  • network design
  • network topology
  • Network topology
  • Probability distribution
  • Reconfigurable networks
  • route length.
  • Routing
  • Topology

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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