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Future Optical Network Architecture

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Presentation on theme: "Future Optical Network Architecture"— Presentation transcript:

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

2 Optical Networks Can we trade bandwidth utilization for lower cost ?
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

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

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 e-switched architecture Computing Optical switching Electronic access Fiber trunks Increasing line speeds Optical access Dispersion managed Limit of WDM/optical switching technology ? Can we trade bandwidth utilization for lower cost ? Vincent Chan

5 Optical Networks Wide area Metro/access
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 Vincent Chan 1 1

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

7 Decreasing cost to scale
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 Vincent Chan

8 Design physical topology
The Optical Network Architect’s Problem 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 100ms can be as fast as 5ms + 1 roundtrip time Vincent Chan

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. Vincent Chan

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 Vincent Chan

11 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

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. Vincent Chan

13 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

14 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

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

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