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

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

2. 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!

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

4. Optical network evolution/revolution and disruptive technologies • 1st disruptive technology - WDM fiber links • 2nd disruptive technology - optical switching • 3rd disruptive technology - direct optical access • 4th disruptive technology - new transport mechanisms Subscriber cost 1 10 102 103 104 105 106 e-switched architecture Computing Optical switching Electronic access 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 ?

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

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

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

8. 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 • 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. Derive desired logical topology (multiple, dynamic) Design sensible fiber plant topology Joint optimization Logical topology realized by routing and wavelength assignment, RWA (dynamic part of LTD) Design physical topology – fixed part of LTD The Optical Network Architect’s Problem 100ms can be as fast as 5ms + 1 roundtrip time

9. 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.

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

11. 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 Routing & Wavelength Assignment and Flow Control Algorithms

12. 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.

13. 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 Algorithms based on state statistics

14. 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 Trade-off between performance, complexity and network dynamics

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