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Next Challenges in Optical Networking Research: . Contribution from the CaON cluster Dimitra Simeonidou: dsimeo@essex.ac.uk , Sergi Figuerola: sergi.figuerola@i2cat.net. The CaON Vision of Future Optical Networks. Application driven and technology enabled. Cloud. Residential.

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next challenges in optical networking research

Next Challenges in Optical Networking Research:

Contribution from the CaON cluster

Dimitra Simeonidou: dsimeo@essex.ac.uk, Sergi Figuerola: sergi.figuerola@i2cat.net

the caon vision of future optical networks
The CaON Vision of Future Optical Networks
  • Application driven and technology enabled

Cloud

Residential

Application Driven

Media

Intelligent

Adaptive Optical Networks

Flexible Network

Flexible use of technology

Elastic use of resources

Technology Enabled

MULTI-BAND

SSS

MULTI-BAND

AMPLIFIER

FAST OPTICAL

SWITCH

SDM

(DE)MUX

MULTI-BAND

SSS

BROADBAND

λ-CONVERSION

High-speed data

400G, 1Tb/s

the caon reference model i
The CaON Reference model I
  • CaON reference model presents a layered architecture linking optical networks with future services and applications
  • The model promotes the convergence of the optical infrastructure layers with upper layers and aims to strategically position optical networks as key enabler of Future Internet and cloud networking service deployment
the caon reference model ii
The CaON Reference model II
  • A bottom-up reference model, where the infrastructure and provisioning layers, together with cross-layer SLA and the management, are identified the key focus for future research trends within the CaON cluster community.
  • The physical infrastructure layer covers from the core to the access optical network technologies.
key research challenges for realizing the caon reference model
Key Research Challenges for Realizing the CaON Reference Model
  • Support for Multi-gigabit Access Rates (FP7 ALPHA, OASIS)
  • Spectrum management: Flexible, Elastic Optical Layer (FP7 STRONGEST, FP7 call 8 IDEALIST)
    • Architectures on Demand
  • Control Plane (FP7 MAINS and STRONGEST)
    • Targeted extensions for dynamic and data plane-aware network services
  • Software/Hardware Defined Network Programmability (FIRE OFELIA and FIRE call 8 ALIEN)
    • For infrastructure and service adaptation
  • Optical Network and IT Convergence (FP7 GEYSERS)
    • Infrastructure Virtualisation, Slicing and Isolation
  • Optical Network Cognition (FP7 CHRON, UK EPSRC Photonics HyperHighway)
  • Energy Efficient Optical Networks (FP7 STRONGEST and TRENT)
spectrum management elastic resource allocation

Flexible allocation of resources in time and frequency in order to:

Accommodate applications with arbitrary requirements

Spectrum Management: Elastic Resource Allocation

Video conference/Virtual Presence

Education/Remote Learning

High-speed data transmission 400G, 1T

Gaming

elastic time and frequency plus space allocation
Elastic Time and Frequency plus Space Allocation
  • Elastic frequency allocation to enable:
    • Support for high-speed channels with arbitrary bandwidth requirements
    • Better spectral efficiency for lower bit rates
  • Elastic time allocation for:
    • Efficient all-optical switching of sub-wavelength traffic
    • Finer all-optical bandwidth granularities

Space

Novel Fibres and Fibre-based components

Continuous channels at various bit-rates

User traffic at various bit-rates and modulation formats

optical networks on demand
Optical Networks on Demand
  • Adapt to traffic profile
  • Support arbitrary switching-granularity
  • Dynamic Infrastructure Composition (including VI)
  • Dynamic architecture reconfiguration
  • Modular infrastructure planning
  • Seamless integration with other technology domains (network + IT)
  • Hitless upgrade with new functionality
    • Wavelength conversion
    • Regeneration
    • Optical signal processing
    • Space division multiplexing (multi-core, multimode)
    • Quantum technologies
    • Other?
support of multi gbps access rates
Support of Multi-Gbps Access Rates:
  • Acceleration of access deployment through
    • Reduced total cost of ownership
    • Converged solutions supporting transport of mobile and fixed traffic in both front- and backhaul scenarios
  • Seamless integration of access and metro/aggregation
    • Unified control and management planes
    • Virtualization and context-aware networking
  • New solutions for simultaneous:
    • More users per feeder (>1000)
    • Higher speeds (up to 10 Gb/s peak)
    • longer reach (100 km)
  • Green and fast (1 Gb/s and beyond) home networking
optical network control plane
Optical network control plane:
  • Main research challenges include
    • True multi-vendor and multi-carrier control plane solutions, including extensions for elastic technologies
    • Split architectures that decouple the control plane from the optical transport
      • OpenFlow as an open/vendor-independent interface to network data plane
      • Multi-technology and multi-domain path computation services coupled with traffic optimization
      • Software Defined Networking at large
    • Control plane interfaces to external end-user “systems” (e.g. clouds) for any type of bandwidth-on-demand service and seamless integration with the service layer workflows.
optical network and it convergence for high performance global reach clouds
Optical Network and IT Convergence: for High Performance, Global Reach Clouds
  • Provisioning over hybrid infrastructures composed of both IT resources (i.e. compute, storage, data centres) and optical networks
  • It will require :
    • Virtualise the physical optical network infrastructure (analogue or digital)
    • Federate heterogeneous resources from different providers
    • Unified management and provisioning procedures for the whole integration with the IT network infrastructures
specific issues in optical network virtualization
Specific Issues in Optical Network Virtualization
  • Optical networks are analogue in nature
    • More complexity than L2/L3 (digital domain) virtualization as a result of physical layer impairments and constraints
    • Slice isolation is a big challenge in optical networks
  • Physical layer impairments
    • Affect the isolation between VIs
    • Newly composed VIs will affect the existing ones
    • Affect the ultimate feasibility of VIs
  • Wavelength continuity constraint
    • Affect the network resource utilization
  • Can we use new infrastructure capabilities such as Space Division Multiplexing (multi-core?)
cognitive self managed optical networks
Cognitive, self managed optical networks:
  • Dynamically re-purpose, evolve, self-adapt and self-optimize functions/devices/systems of the optical network.
    • Optical/opto-electronic technologies that would allow for environment-aware systems that can change any parameter based on interaction with the environment with or without user assistance
    • Cognitive control and management plane for dynamic infrastructure self-adaptation across heterogeneous systems.
energy efficient optical networking
Energy efficient optical networking:
  • Improve the design, planning and operations for energy aware management capable of 100 times energy consumption reduction
    • Introduction of new simpler protocols
    • Definition of energy friendly resilience
    • Support of planning and routing algorithms
  • Focus on energy efficient optical network services for applications such as P2P, grid or cloud services