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Future Optical Network Architecture Vincent Chan, Asuman Ozdaglar, Devavrat Shah MIT NSF FIND Meeting Nov 2006 PowerPoint Presentation
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Future Optical Network Architecture Vincent Chan, Asuman Ozdaglar, Devavrat Shah MIT NSF FIND Meeting Nov 2006. Optical Networks. WDM, Optical amplifiers  high rates, long reach multicasting

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slide1

Future Optical Network Architecture

Vincent Chan, Asuman Ozdaglar, Devavrat Shah

MIT

NSF FIND Meeting Nov 2006

slide2

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!

slide3

Optical Network – Near future

  • Optical switching – GMPLS bypass, load balancing, …
  • Packet processing cost dominates
slide4

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 ?

slide5

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

slide6

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)

slide7

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

slide8

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

slide9

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.

slide10

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
slide11
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

slide12

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.
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

Algorithms based on state statistics
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

Trade-off between performance, complexity and network dynamics
slide15

‘New technology’

  • New transport mechanisms
  • New architectures
  • New applications
  • Grows faster than Moore’s Law
  • New opportunities