ReasoNet: Inferring Network Policies Using Ontologies

Charalampos Rotsos; Arsham Farshad; Daniel King; David Hutchison; Qianru Zhou; Alasdair J. G. Gray; Cheng-Xiang Wang; Stephen McLaughlin

doi:10.1109/NETSOFT.2018.8460050

ReasoNet: Inferring Network Policies Using Ontologies

Charalampos Rotsos, Arsham Farshad, Daniel King, David Hutchison, Qianru Zhou, Alasdair J. G. Gray, Cheng-Xiang Wang, Stephen McLaughlin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Citations (Scopus)

99 Downloads (Pure)

Abstract

Modern Software Defined Networking (SDN) control stacks consist of multiple abstraction and virtualization layers to enable flexibility in the development of new control features. Rich data modeling frameworks are essential when sharing information across control layers. Unfortunately, existing Network Operating System (NOS) data modeling capabilities are limited to simple type-checking and code templating. We present an exploration of a more extreme point on SDN data modeling: ReasoNet. Developers can use semantic web technologies to enrich their data models with reasoning rules and integrity/consistency constraints, and automate state inference across layers. We demonstrate the ability of ReasoNet to automate state verification and cross-layer debugging, through the implementation of two popular control applications, a learning switch and a Quality of Service (QoS) policy engine.

Original language	English
Title of host publication	2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft)
Publisher	IEEE
Pages	217-221
Number of pages	5
ISBN (Electronic)	9781538646335
DOIs	https://doi.org/10.1109/NETSOFT.2018.8460050
Publication status	Published - 13 Sept 2018
Event	4th IEEE Conference on Network Softwarization and Workshops 2018 - Montreal, Canada Duration: 25 Jun 2018 → 29 Jun 2018

Conference

Conference	4th IEEE Conference on Network Softwarization and Workshops 2018
Abbreviated title	NetSoft 2018
Country/Territory	Canada
City	Montreal
Period	25/06/18 → 29/06/18

ASJC Scopus subject areas

Computer Networks and Communications
Software
Safety, Risk, Reliability and Quality

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10.1109/NETSOFT.2018.8460050

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Cite this

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title = "ReasoNet: Inferring Network Policies Using Ontologies",

abstract = "Modern Software Defined Networking (SDN) control stacks consist of multiple abstraction and virtualization layers to enable flexibility in the development of new control features. Rich data modeling frameworks are essential when sharing information across control layers. Unfortunately, existing Network Operating System (NOS) data modeling capabilities are limited to simple type-checking and code templating. We present an exploration of a more extreme point on SDN data modeling: ReasoNet. Developers can use semantic web technologies to enrich their data models with reasoning rules and integrity/consistency constraints, and automate state inference across layers. We demonstrate the ability of ReasoNet to automate state verification and cross-layer debugging, through the implementation of two popular control applications, a learning switch and a Quality of Service (QoS) policy engine.",

author = "Charalampos Rotsos and Arsham Farshad and Daniel King and David Hutchison and Qianru Zhou and Gray, {Alasdair J. G.} and Cheng-Xiang Wang and Stephen McLaughlin",

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doi = "10.1109/NETSOFT.2018.8460050",

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booktitle = "2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft)",

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note = "4th IEEE Conference on Network Softwarization and Workshops 2018, NetSoft 2018 ; Conference date: 25-06-2018 Through 29-06-2018",

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Rotsos, C, Farshad, A, King, D, Hutchison, D, Zhou, Q, Gray, AJG, Wang, C-X & McLaughlin, S 2018, ReasoNet: Inferring Network Policies Using Ontologies. in 2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft). IEEE, pp. 217-221, 4th IEEE Conference on Network Softwarization and Workshops 2018, Montreal, Canada, 25/06/18. https://doi.org/10.1109/NETSOFT.2018.8460050

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AU - Rotsos, Charalampos

AU - Farshad, Arsham

AU - King, Daniel

AU - Hutchison, David

AU - Zhou, Qianru

AU - Gray, Alasdair J. G.

AU - Wang, Cheng-Xiang

AU - McLaughlin, Stephen

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AB - Modern Software Defined Networking (SDN) control stacks consist of multiple abstraction and virtualization layers to enable flexibility in the development of new control features. Rich data modeling frameworks are essential when sharing information across control layers. Unfortunately, existing Network Operating System (NOS) data modeling capabilities are limited to simple type-checking and code templating. We present an exploration of a more extreme point on SDN data modeling: ReasoNet. Developers can use semantic web technologies to enrich their data models with reasoning rules and integrity/consistency constraints, and automate state inference across layers. We demonstrate the ability of ReasoNet to automate state verification and cross-layer debugging, through the implementation of two popular control applications, a learning switch and a Quality of Service (QoS) policy engine.

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ReasoNet: Inferring Network Policies Using Ontologies

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Conference

ASJC Scopus subject areas

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