An Integration of Ontology-based and Policy-based Network Management for Automation

Xiao, Di; Xu, Hui

doi:10.1109/cimca.2006.43

Cited by 13 publications

(3 citation statements)

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“…In [16], an ontology is presented to model service operator policies to represent both the data and relationships between the data for all stakeholder views. The ontology design presented in this paper complements the designs presented in [15] and [16] but focuses more on a way to optimize the QoE of running services. Furthermore, we use the SWRL rule language to deduce additional information and introduce autonomic behavior.…”

Section: Related Workmentioning

confidence: 88%

“…In the domain of network management, ontologies have also been proposed. The authors of [15] argue that ontologies alone do not suffice to perform a complete network management and use a combination of an ontology model and policies. In [16], an ontology is presented to model service operator policies to represent both the data and relationships between the data for all stakeholder views.…”

Section: Related Workmentioning

confidence: 98%

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Design for a Generic Knowledge Base for Autonomic QoE Optimization in Multimedia Access Networks

Latré

Simoens

Vleeschauwer

et al. 2008

NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops

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The management of access networks to guarantee the Quality of Experience for multiplay services, is complicated by the heterogeneity in service specifics and home network configurations. The appropriate action to restore the QoE is highly dependent on the type of service, the affected user, etc. This requires an almost per-user and per-service management. Through autonomous reasoning, the required QoE restorative actions for underperforming services can be determined in a scalable way. This reasoning process needs a solid knowledge base, containing information about the network, the services and the QoE restorative actions that can be undertaken. This article gives an overview of these requirements and presents an OWL/SWRL based knowledge base that can be used in an autonomous QoE management architecture for the access network. Besides storing all information, the proposed knowledge base will autonomously deduce new information. This new information can be used to raise alarms to higher layers in the architecture or to autonomously propose QoE restorative actions for underperforming services.

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Section: Related Workmentioning

confidence: 88%

Section: Related Workmentioning

confidence: 98%

Design for a Generic Knowledge Base for Autonomic QoE Optimization in Multimedia Access Networks

Latré

Simoens

Vleeschauwer

et al. 2008

NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops

View full text Add to dashboard Cite

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“…An OWL ontology can be used as the integration of all domain information, when at the same time, Merge and Map (M&M) methods must also be taken into account [15] [16] [17]. A step forward in integrating ontology-based information is to add behavior information, to the OWL ontology using SWRL [18] [19]. Moreover, OWL-S is an ontology developed in Semantic Web domain, aiming at the automatic discovery, invocation, composition and interoperation of Web services, and it can be utilized to promote the automation of network management [20].…”

Section: B Integration In a Unified Mannermentioning

confidence: 99%

Semantic Management Information Modeling based on Theory of Concept Lattices

Xu¹,

Wang²,

Chen³

et al. 2010

IJMECS

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With the development of future Internet, it is of great significance to study how to realize unified management information modeling, in order to avoid a lot of repetitive work and standardize information modeling in network management domain. This paper discusses the problem from the ontology point of view and introduces the theory of concept lattices into the research on semantic management information modeling, which includes a) establishing an ontology-driven framework for semantic management information modeling, b) building unified management information modeling ontology based on concept lattices, and c) generating semantic models for network management information modeling using the theory of concept lattices. . Currently, his major field of study is computational intelligence.

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