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Vincent Chan1 Future Optical Network Architecture Vincent Chan, Asuman Ozdaglar, Devavrat Shah MIT NSF FIND Meeting Nov 2006.

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Presentation on theme: "Vincent Chan1 Future Optical Network Architecture Vincent Chan, Asuman Ozdaglar, Devavrat Shah MIT NSF FIND Meeting Nov 2006."— Presentation transcript:

1 Vincent Chan1 Future Optical Network Architecture Vincent Chan, Asuman Ozdaglar, Devavrat Shah MIT NSF FIND Meeting Nov 2006

2 Vincent Chan2 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 Vincent Chan3 Optical Network – Near future Optical switching – GMPLS bypass, load balancing, … Packet processing cost dominates

4 Vincent Chan4 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 2014 2018 2020 Fiber trunks Increasing line speeds Dispersion managed e-switched architecture Optical switching 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 Electronic access Optical access Limit of WDM/optical switching technology ? Optical network evolution/revolution and disruptive technologies Computing 1 10 10 2 10 3 10 4 10 5 10 6 Subscriber cost Can we trade bandwidth utilization for lower cost ?

5 Vincent Chan5 Optical Networks CO AN Distribution Rings Access Node Distribution Tree Metro/access Wide area Feeder Distribution bus Physical and logical architecture Transport mechanisms –flow switching Routing: separate IP and optical control planes Very fast dynamics < 100mS Scalable Low cost

6 Vincent Chan6 Optical flow switching (OFS) Electronic packet switching (EPS) Generalized multiprotocol label switching (GMPLS) Tell-and-Go / burst switching (TaG) Candidate Transport Mechanisms LAN mux WAN w dedicated wavelength channels X X OXC X X LAN mux scheduler WAN w dedicated wavelength channels X X OXC X X WAN MAN LAN WAN router MAN router WAN MAN LAN w dedicated wavelength channels MAN router X X OXC WAN router

7 Vincent Chan7 Optical Flow Switching and Bypass User 1User 2 Router 1 Router 2 Router 3 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 WDM layer... Network control Decreasing cost to scale

8 Vincent Chan8 T Given dynamic traffic matrices Derive desired logical topology (multiple, dynamic) Design sensible fiber plant topology Design physical topology – fixed part of LTD Logical topology realized by routing and wavelength assignment, RWA (dynamic part of LTD) 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. Joint optimization The Optical Network Architects Problem 100ms can be as fast as 5ms + 1 roundtrip time

9 Vincent Chan9 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. Cost comparison of transport mechanisms

10 Vincent Chan10 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 Large reconfigurable optical switches as architecture building blocks

11 Vincent Chan11 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 Vincent Chan12 Optimal multi-commodity flow formulation f l : 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. Multi-commodity Flow Formulation

13 Vincent Chan13 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

14 Vincent Chan14 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 Vincent Chan15 New technology New transport mechanisms New architectures New applications Grows faster than Moores Law New opportunities

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