Network optimization for unified packet and circuit switched networks

Internet traffic continues to grow relentlessly, driven largely by increasingly high resolution video content. Although studies have shown that the majority of packets processed by Internet routers are pass-through traffic, they nonetheless have to be queued and routed at every hop in current networ...

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Bibliographic Details
Published in:Optimization and engineering 2020-03, Vol.21 (1), p.159-180
Main Authors: Yin, Ping, Diamond, Steven, Lin, Bill, Boyd, Stephen
Format: Article
Language:English
Subjects:
Circuits
Control
Convexity
Engineering
Environmental Management
Financial Engineering
Mathematics
Mathematics and Statistics
Network management systems
Operations Research/Decision Theory
Optical communication
Optimization
Queues
Research Article
Routers
Switching theory
Systems Theory
Traffic capacity
Traffic flow
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Summary:Internet traffic continues to grow relentlessly, driven largely by increasingly high resolution video content. Although studies have shown that the majority of packets processed by Internet routers are pass-through traffic, they nonetheless have to be queued and routed at every hop in current networks, which unnecessarily adds substantial delays and processing costs. Such pass-through traffic can be better circuit-switched through the underlying optical transport network by means of pre-established circuits, which is possible in a unified packet and circuit switched network. In this paper, we propose a novel convex optimization framework based on a new destination-based multicommodity flow formulation for the allocation of circuits in such unified networks. In particular, we consider two deployment settings, one based on real-time traffic monitoring, and the other relying upon history-based traffic predictions. In both cases, we formulate global network optimization objectives as concave functions that capture the fair sharing of network capacity among competing traffic flows. The convexity of our problem formulations ensures globally optimal solutions.
ISSN:1389-4420
1573-2924
DOI:10.1007/s11081-019-09439-0