Towards a Self-Organizing Model for Virtual Network

Provisioning

Master’s Thesis ProposalCarolina Valadares and Carlos Lucena

2013/I

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The Problem

Network Ossification

High dependence on human intervention for configuration and troubleshooting.

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The Problem

Network Ossification

High dependence on human intervention for configuration and troubleshooting.

Virtual Networks

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Proposed Solution

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Proposed Solution

Physical Network

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Proposed Solution

Physical Network

Physical Router

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Proposed Solution

Physical Network

Physical Link

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Proposed Solution

Virtual Network

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Proposed Solution

Virtual Network

Virtual Router

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Proposed Solution

Virtual Network

Virtual Link

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Proposed Solution

Two main characteristics:- Adaptation

- Physical Resource Sharing

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Environment Changes

Virtual Router Overload/ Virtual Router Failure

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Environment Changes

Unbalanced Virtual Links

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Environment Changes

Physical Router Overload/ Physical Router Failure

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Proposed Solution

Autonomic Agents

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Proposed Solution

Agent Communication

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Self-Organizing Model

Adaptive Plans: Replace Virtual Machine Live Migrate Virtual Machine Balance virtual link

• With and without the creation of new virtual machine

Custom Control Loop (IBM extension): Collector; Analyzer; Decision-Maker; Norm Checker; and Executor.

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Self-Organizing Model

Self-Organizing Monitoring:

• Event-based and on demand; • Dynamic adjustment of a set of parameters (Norms).

Analyzing: • State-based and history-based; • Use of metrics; • Uses up-to-date knowledge about its current status.

Decision Making:• Triggered in response to external or internal event;• Apply the most appropriate decisions without any human support ; • Adaptation rate.

Norms Self-Tuning Reputation

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Self-Organizing Model

Self-Awareness Knowledge representation

• Structure knowledge• Behavior knowledge• Adaptive Plans Knowledge

knowledge acquiring: (Inferred knowledge)• Infers current virtual and physical network topology; • Infers event execution; • Infers network status;• Implicit coordination.• Discovering knowledge existence.

Knowledge sharing• Exchange messages only in the neighborhood.

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Self-Organizing Model

Norms/Reputation Self-Tuning:

• Dynamic adjustment of a set of parameters (minor adaptation operations – Control Loop parameter tuning)

Reputation:• To support the live migration of virtual routers, the

decision maker takes into account the link Stress together with the Entities’ Reputation – popularity, rather than only Network parameters.

• History-based to describe the requests rate of a virtual/physical router.

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Next Directions

ReputationSelf-awareness Experiments

E01: Self-Organizing E02: Self-Organizing and Self-Awareness E03: Self-Organizing, Self-Awareness and Self-

Tuning E04: Final Experiment with Self-Organizing,

Reputation, Self-Awareness and Self-Tuning

Cross-Validation Ei vs. Baseline

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Chronogram

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References

[1] C. Prehofer and C. Bettstetter, “Self-organization in communication networks: Principles and design paradigms”, IEEE Communications, 2005.

[2] Z. Movahedi et al., "A Survey of Autonomic Network Architectures and Evaluation Criteria”, Communications Surveys & Tutorials, IEEE, 2012.

[3] Ines Houidi , Wajdi Louati , Djamal Zeghlache , Panagiotis Papadimitriou , Laurent Mathy, "Adaptive virtual network provisioning”, Proceedings of the second ACM SIGCOMM workshop on Virtualized infrastructure systems and architectures, 2010.

Questions?

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