Future Optical Network Architecture Vincent Chan Asuman Ozdaglar

Future Optical Network Architecture Vincent Chan, Asuman Ozdaglar, Devavrat Shah MIT NSF FIND Meeting Nov 2006 Vincent Chan 1

Optical Networks • WDM, Optical amplifiers high rates, long reach multicasting • Optical routing and switching power localization, narrow casting, long reach, high utilization? • Increase in capacities (major difference between fiber bandwidth and link rates) decrease in cost? Can we trade bandwidth utilization for lower cost ? Perhaps but with new architectures! Vincent Chan 2

Optical Network – Near future • Optical switching – GMPLS bypass, load balancing, … • Packet processing cost dominates Vincent Chan 3

• 1 st disruptive technology - WDM fiber links • 2 nd disruptive technology - optical switching • 3 rd disruptive technology - direct optical access • 4 th disruptive technology - new transport mechanisms Subscriber cost e-switched architecture Computing Optical switching Electronic access 10 102 103 104 105 106 Optical network evolution/revolution and disruptive technologies 1 Fiber trunks Increasing line speeds Optical access Dispersion managed Limit of WDM/optical switching technology ? 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 2014 2018 2020 Can we trade bandwidth utilization for lower cost ? Vincent Chan 4

Optical Networks Wide area CO Metro/access Feeder • Transport mechanisms –flow switching AN Distribution Tree AN • Physical and logical architecture AN • Routing: separate IP and optical control planes • Very fast dynamics < 100 m. S AN Distribution Rings AN Access Node • Scalable • Low cost Distribution bus Vincent Chan 5

Candidate Transport Mechanisms scheduler WAN LAN X X mux OXC X w dedicated wavelength channels WAN LAN X X mux X Tell-and-Go / burst switching (Ta. G) OXC X w dedicated wavelength channels X Optical flow switching (OFS) WAN MAN router LAN MAN WAN router LAN X LAN OXC X w dedicated wavelength channels MAN Generalized multiprotocol label switching (GMPLS) Vincent Chan MAN router MAN WAN router WAN MAN Electronic packet switching (EPS) 6

Optical Flow Switching and Bypass User 1 Network control . . . Router 1 User 2 . . . Router 2 Router 3 WDM layer • End-to end (user-to-user) flows bypassing routers • Very challenging IP/optical control planes (<100 ms) • Architecture provide multiple services including overlays. • Supports virtualization • Security? Optical infrastructure isolation Vincent Chan Decreasing cost to scale 7

The Optical Network Architect’s Problem T Given dynamic traffic matrices • When failure occurs or traffic changes, tunable XCR & OXC take care of maintaining or providing new logical connection via RWA Derive desired logical topology (multiple, dynamic) Design sensible fiber plant topology Joint optimization • When needed physical topology fixed part of LTD can be redone to get better connections when traffic changes • Physical topology is made changeable by OXC, slow or fast. Vincent Chan Logical topology realized by routing and wavelength assignment, RWA (dynamic part of LTD) Design physical topology – fixed part of LTD 100 ms can be as fast as 5 ms + 1 roundtrip time 8

Cost comparison of transport mechanisms This plot assumes that there are 10, 000 users per MAN, including both active and dormant users. It is assumed that 10% of the number of users in each MAN are active (i. e. transmitting) at any instant in time. It is also assumed that MAN and WAN routers run at 20% utilization. Vincent Chan 9

Large reconfigurable optical switches as architecture building blocks • Large optical switches used for aggregation and multi/narrow-cast • Reconfigurable at m. S rates • Allows dynamic group formation for active flow switching users • Optical multicast create new reachable regions with networking coding • Simplifies hardware Vincent Chan 10

Routing & Wavelength Assignment and Flow Control Algorithms • Two main challenges in the design of routing and flow control mechanisms: – Design of distributed asynchronous algorithms that work with local information – Nonconvexities due to integrality constraints, and nonlinear dependencies on the lightpaths owing to fiber nonlinearities. • Previous Work: RWA problem formulated as a mixed integer-linear program (computationally very hard) • Two approaches: – Multi-commodity flow formulation – Statistical techniques for routing, scheduling and admission control Vincent Chan 11

Multi-commodity Flow Formulation • Optimal multi-commodity flow formulation • fl : Total flow of link l • The link cost function convex and monotonically increasing – Keep link flows away from link capacity – The link cost function piecewise linear with integer breakpoints • We proved in some topologies that the relaxed problem has an integer optimal solution and provided an efficient algorithm to find it. Vincent Chan 12

Algorithms based on state statistics • Algorithms need to operate at the granularity of flows • Primary network layer tasks in flow-level network – Admission control • Buffering, admitting or dropping flows arriving at network • Interacts with Routing and Scheduling to make decisions – Routing and wavelength scheduling • Assign rates to end-hosts at network layer based on available statistical information • Given rate requirement by interacting with routing, it allocates physical resources such as lightpaths and wavelengths to end-hosts Vincent Chan 13

Trade-off between performance, complexity and network dynamics • The algorithms utilize statistical information about network – Dynamics of network affects the confidence in statistical information – Complexity of feedback can reduce effect of dynamics Trade-off between complexity and effect of dynamics • The confidence in statistical information affects performance – Less accurate statistical information will lead to wastage of resources • Thus, for algorithms operating in such network – Trade-off between performance, complexity and network dynamics plays an important role in design • Traffic statistics collection algorithms are essential in the network performance Vincent Chan 14

• ‘New technology’ • New transport mechanisms • New architectures • New applications • Grows faster than Moore’s Law • New opportunities Vincent Chan 15