TY - JOUR

T1 - Demand-aware network designs of bounded degree

AU - Avin, Chen

AU - Mondal, Kaushik

AU - Schmid, Stefan

N1 - Funding Information:
This work was supported by the German-Israeli Foundation for Scientific Research (GIF) Grant I-1245-407.6/2014. We would like to thank Michael Elkin for many inputs and discussions and also the anonymous reviewers whose comments helped us to improve this manuscript.
Publisher Copyright:
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

PY - 2020/6/1

Y1 - 2020/6/1

N2 - Traditionally, networks such as datacenter interconnects are designed to optimize worst-case performance under arbitrary traffic patterns. Such network designs can however be far from optimal when considering the actual workloads and traffic patterns which they serve. This insight led to the development of demand-aware datacenter interconnects which can be reconfigured depending on the workload. Motivated by these trends, this paper initiates the algorithmic study of demand-aware networks, and in particular the design of bounded-degree networks. The inputs to the network design problem are a discrete communication request distribution, D, defined over communicating pairs from the node set V, and a bound, Δ, on the maximum degree. In turn, our objective is to design an (undirected) demand-aware network N= (V, E) of bounded-degree Δ, which provides short routing paths between frequently communicating nodes distributed across N. In particular, the designed network should minimize the expected path length on N (with respect to D), which is a basic measure of the efficiency of the network. We derive a general lower bound based on the entropy of the communication pattern D, and present asymptotically optimal demand-aware network design algorithms for important distribution families, such as sparse distributions and distributions of locally bounded doubling dimensions.

AB - Traditionally, networks such as datacenter interconnects are designed to optimize worst-case performance under arbitrary traffic patterns. Such network designs can however be far from optimal when considering the actual workloads and traffic patterns which they serve. This insight led to the development of demand-aware datacenter interconnects which can be reconfigured depending on the workload. Motivated by these trends, this paper initiates the algorithmic study of demand-aware networks, and in particular the design of bounded-degree networks. The inputs to the network design problem are a discrete communication request distribution, D, defined over communicating pairs from the node set V, and a bound, Δ, on the maximum degree. In turn, our objective is to design an (undirected) demand-aware network N= (V, E) of bounded-degree Δ, which provides short routing paths between frequently communicating nodes distributed across N. In particular, the designed network should minimize the expected path length on N (with respect to D), which is a basic measure of the efficiency of the network. We derive a general lower bound based on the entropy of the communication pattern D, and present asymptotically optimal demand-aware network design algorithms for important distribution families, such as sparse distributions and distributions of locally bounded doubling dimensions.

UR - http://www.scopus.com/inward/record.url?scp=85066493443&partnerID=8YFLogxK

U2 - 10.1007/s00446-019-00351-5

DO - 10.1007/s00446-019-00351-5

M3 - Article

AN - SCOPUS:85066493443

SN - 0178-2770

VL - 33

SP - 311

EP - 325

JO - Distributed Computing

JF - Distributed Computing

IS - 3-4

ER -