Predictive risk awareness for proactive management IETF92 Dallas - - PowerPoint PPT Presentation

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Predictive risk awareness for proactive management IETF92 Dallas - - PowerPoint PPT Presentation

Feb 22, 2024 207 likes •321 views

Predictive risk awareness for proactive management IETF92 Dallas Bruno Vidalenc, Laurent Ciavaglia 1 History Concept and mechanism presented at NMRG IETF89-London http://www.ietf.org/proceedings/89/slides/slides-89-nmrg-1.pdf Use

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Predictive risk awareness for proactive management

IETF92 – Dallas Bruno Vidalenc, Laurent Ciavaglia

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History

  • Concept and mechanism presented at NMRG

IETF89-London

http://www.ietf.org/proceedings/89/slides/slides-89-nmrg-1.pdf

  • Use case presented at UCAN BoF IETF90-

Toronto

http://www.ietf.org/proceedings/90/slides/slides-90-ucan-2.pdf

  • Today: towards an ANIMA-compliant ASA?

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Mechanism recap

Risk Level Assessment Adaptive OSPF Failure Detection Timers Adaptive Level of Recovery Risk Level Risk Level Risk Level Risk-Aware Routing

Probes (e.g. T°)

3 Load, Events, Traffic…

  • 3. Trigger actions
  • 4. Learn

feedback feedback feedback

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Mechanism recap

Risk Level Assessment Adaptive OSPF Failure Detection Timers Adaptive Level of Recovery Risk Level Risk Level Risk Level Risk-Aware Routing

Probes (e.g. T°)

4 Load, Events, Traffic…

  • 1. Collect data
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SLIDE 5

Mechanism recap

Risk Level Assessment Adaptive OSPF Failure Detection Timers Adaptive Level of Recovery Risk Level Risk Level Risk Level Risk-Aware Routing

Probes (e.g. T°)

5 Load, Events, Traffic…

  • 1. Collect data
  • 2. Compute risk
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SLIDE 6

Mechanism recap

Risk Level Assessment Adaptive OSPF Failure Detection Timers Adaptive Level of Recovery Risk Level Risk Level Risk Level Risk-Aware Routing

Probes (e.g. T°)

6 Load, Events, Traffic…

  • 1. Collect data
  • 2. Compute risk
  • 3. Trigger actions
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SLIDE 7

Mechanism recap

Risk Level Assessment Adaptive OSPF Failure Detection Timers Adaptive Level of Recovery Risk Level Risk Level Risk Level Risk-Aware Routing

Probes (e.g. T°)

7 Load, Events, Traffic…

  • 1. Collect data
  • 2. Compute risk
  • 3. Trigger actions
  • 4. Learn

feedback feedback feedback

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Notes

  • Learning to improve process accuracy, utility over time
  • Local

– Local decision-based – Local device information/monitoring – Distributed execution

  • Global

– Mitigate local instabilities – Deeper risk “understanding” thanks to correlation/context awareness – Local/global risk information/patterns for other mechanisms

  • Time window

– Big (hours) preventive maintenance (e.g. field interventions) – Small (seconds)  automatic mechanisms (restoration/protection, cold stand-by activation…)

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(tentative) Mapping to reference model

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(tentative) Mapping to reference model

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Risk-aware mechanism sensing triggers, commands e.g. fault management strategy e.g. interactions w/ other (risk-aware) mechanisms (not mandatory) Risk assessment risk level

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Discuss: ANIMA compliance/impact

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  • Ability to anticipate on future network condition/context

– a new capability of interest to many mechanisms

  • How to make it accessible and useful for other ASAs?

– common components, place in the reference model, interfaces...

  • How to design a generic yet customizable functionality (via

intent, capability-aware) and not replicate per function/service?

  • Common way(s) to connect to information sources…
  • Common way(s) to disseminate risk information to target

functions/agents…

  • Common way(s) to learn/build knowledge but also store,

query, process…

  • Interfaces to GDNP...? Specify GDNP objectives...?