Constraint-based configuration complexity model for autonomic network configuration management

Deca, Rudy; Cherkaoui, Omar; Savaria, Yvon

doi:10.1109/giis.2014.6934272

Cited by 1 publication

(7 citation statements)

References 14 publications

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“…In this paper, we assess the influence of these factors and features on rule efficiency and overall error coverage, with a case study that includes various network sizes and multiple services. We also provide further confirmation of the correlation found in [28] for different services and variable network-level complexity factors.…”

Section: Related Worksupporting

confidence: 79%

“…This can be done by fine-tuning the descriptive rule features using the following operations: (i) replacing structure rules with value ones; (ii) replacing local rules with global ones; (iii) replacing more permissive applicability quantifiers with stricter ones; and (iv) widening the rule scope. Note that these actions can also increase rule execution complexity [28]. Consequently, when optimising the validation process, we need to find the right trade-off between rule's efficiency and execution complexity.…”

Section: B Rule-level Resultsmentioning

confidence: 99%

“…In [28], we proposed a complexity model for the rulebased network service provisioning tasks and illustrated its use in a small service validation case study. In numerical examples, we determined the influence of the networklevel complexity factors and rule descriptive features on the rule execution complexity.…”

Section: Related Workmentioning

confidence: 99%

“…The Rule-Based Configuration Complexity Model [28] -proposes a hierarchical set of metrics to quantify the complexity of network service provisioning tasks. The defined metrics have four levels of granularity, which are described below.…”

Section: Provisioning Rules and Configuration Information Modelmentioning

confidence: 99%

“…In [28], we studied the correlation between rule efficiency and complexity. We expressed it using a simple equation:…”

Section: Correlation Between Efficiency and Complexity Measuresmentioning

confidence: 99%

See 4 more Smart Citations

Rule-Based Network Service Provisioning

Deca¹,

Cherkaoui²,

Savaria³

2012

JNW

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Due to the unprecedented development of networks, manual network service provisioning is becoming increasingly risky, error-prone, expensive, and time-consuming. To solve this problem,rule-based methods can provide adequate leverage for automating various network management tasks. This paper presents a rule-based solution for automated network service provisioning. The proposed approach captures configuration data interdependencies using high-level, service-specific, user-configurable rules. We focus on the service validation task, which is illustrated by means of a case study.

Based on numerical results, we analyse the influence of the network-level complexity factors and rule descriptive features on the rule efficiency. This analysis shows the operators how to increase rule efficiency while keeping the rules simple and the rule set compact. We present a technique that allows operators to increase the error coverage, and we show that high error coverage scales well when the complexity of networks and services increases.
We reassess the correlation function between specific rule efficiency and rule complexity metrics found in previous work, and show that this correlation function holds for various sizes, types, and complexities of networks and services.

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Section: Related Worksupporting

confidence: 79%

Section: B Rule-level Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Provisioning Rules and Configuration Information Modelmentioning

confidence: 99%

“…In [28], we studied the correlation between rule efficiency and complexity. We expressed it using a simple equation:…”

Section: Correlation Between Efficiency and Complexity Measuresmentioning

confidence: 99%