Robust Network Design for Software-Defined IP/Optical Backbones

Recently, Internet service providers (ISPs) have gained increased flexibility in how they configure their in-ground optical fiber into an IP network. This greater control has been made possible by (i) the maturation of software defined networking (SDN), and (ii) improvements in optical switching technology. Whereas traditionally, at network design time, each IP link was assigned a fixed optical path and bandwidth, modern colorless and directionless Reconfigurable Optical Add/Drop Multiplexers (CD ROADMs) allow a remote SDN controller to remap the IP topology to the optical underlay on the fly. Consequently, ISPs face new opportunities and challenges in the design and operation of their backbone networks. Specifically, ISPs must determine how best to design their networks to take advantage of the new capabilities; they need an automated way to generate the least expensive network design that still delivers all offered traffic, even in the presence of equipment failures. This problem is difficult because of the physical constraints governing the placement of optical regenerators, a piece of optical equipment necessary for maintaining an optical signal over long stretches of fiber. As a solution, we present an integer linear program (ILP) which (1) solves the equipment-placement network design problem; (2) determines the optimal mapping of IP links to the optical infrastructure for any given failure scenario; and (3) determines how best to route the offered traffic over the IP topology. To scale to larger networks, we also describe an efficient heuristic that finds nearly optimal network designs in a fraction of the time. Further, in our experiments our ILP offers cost savings of up to 29% compared to traditional network design techniques.

[1]  Gagan Choudhury,et al.  Real-Time Traffic Management in AT&T's SDN-Enabled Core IP/Optical Network , 2018, 2018 Optical Fiber Communications Conference and Exposition (OFC).

[2]  Robert D. Doverspike,et al.  Restoration Design in IP over Reconfigurable All-Optical Networks , 2007, NPC.

[3]  David Lynch,et al.  Two use cases of machine learning for SDN-enabled ip/optical networks: traffic matrix prediction and optical path performance prediction [Invited] , 2018, IEEE/OSA Journal of Optical Communications and Networking.

[4]  Kang Xi,et al.  Evolving to an SDN-enabled isp backbone: key technologies and applications , 2016, IEEE Communications Magazine.

[5]  Wei Xu,et al.  Optimizing Bulk Transfers with Software-Defined Optical WAN , 2016, SIGCOMM.

[6]  J. Strand,et al.  Joint IP/optical layer restoration after a router failure , 2001, OFC 2001. Optical Fiber Communication Conference and Exhibit. Technical Digest Postconference Edition (IEEE Cat. 01CH37171).

[7]  Eytan Modiano,et al.  Dynamic reconfiguration and routing algorithms for IP-over-WDM networks with stochastic traffic , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[8]  Dahai Xu,et al.  Architectures and Protocols for Capacity Efficient, Highly Dynamic and Highly Resilient Core Networks [Invited] , 2012, IEEE/OSA Journal of Optical Communications and Networking.