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Title: | Demand-aware network design with minimal congestion and route lengths |
Authors: | Avin, C. Mondal, K. Schmid, S. |
Keywords: | approximation algorithms Data centers Entropy IEEE transactions load network design network topology Network topology Probability distribution Reconfigurable networks route length. Routing; Topology |
Issue Date: | 15-Jul-2022 |
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). |
URI: | http://localhost:8080/xmlui/handle/123456789/3624 |
Appears in Collections: | Year-2022 |
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