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ReasoNet: Inferring Network Policies Using Ontologies

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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ReasoNet : Inferring Network Policies Using Ontologies. / Rotsos, Charalampos; Farshad, Arsham; King, Daniel; Hutchison, David.

2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft). IEEE, 2018. p. 159-167.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Rotsos, C, Farshad, A, King, D & Hutchison, D 2018, ReasoNet: Inferring Network Policies Using Ontologies. in 2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft). IEEE, pp. 159-167, IEEE Conference on Network Softwarization, Montreal, Canada, 25/06/18. https://doi.org/10.1109/NETSOFT.2018.8460050

APA

Rotsos, C., Farshad, A., King, D., & Hutchison, D. (2018). ReasoNet: Inferring Network Policies Using Ontologies. In 2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft) (pp. 159-167). IEEE. https://doi.org/10.1109/NETSOFT.2018.8460050

Vancouver

Rotsos C, Farshad A, King D, Hutchison D. ReasoNet: Inferring Network Policies Using Ontologies. In 2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft). IEEE. 2018. p. 159-167 https://doi.org/10.1109/NETSOFT.2018.8460050

Author

Rotsos, Charalampos ; Farshad, Arsham ; King, Daniel ; Hutchison, David. / ReasoNet : Inferring Network Policies Using Ontologies. 2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft). IEEE, 2018. pp. 159-167

Bibtex

@inproceedings{344fa325e66a408e85c9ef575451f551,
title = "ReasoNet: Inferring Network Policies Using Ontologies",
abstract = "Modern 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 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 QoS policy engine.",
author = "Charalampos Rotsos and Arsham Farshad and Daniel King and David Hutchison",
note = "{\textcopyright}2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.; IEEE Conference on Network Softwarization, IEEE NetSoft ; Conference date: 25-06-2018 Through 29-06-2018",
year = "2018",
month = sep,
day = "13",
doi = "10.1109/NETSOFT.2018.8460050",
language = "English",
pages = "159--167",
booktitle = "2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft)",
publisher = "IEEE",
url = "http://netsoft2018.ieee-netsoft.org/",

}

RIS

TY - GEN

T1 - ReasoNet

T2 - IEEE Conference on Network Softwarization

AU - Rotsos, Charalampos

AU - Farshad, Arsham

AU - King, Daniel

AU - Hutchison, David

N1 - Conference code: 4

PY - 2018/9/13

Y1 - 2018/9/13

N2 - Modern 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 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 QoS policy engine.

AB - Modern 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 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 QoS policy engine.

U2 - 10.1109/NETSOFT.2018.8460050

DO - 10.1109/NETSOFT.2018.8460050

M3 - Conference contribution/Paper

SP - 159

EP - 167

BT - 2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft)

PB - IEEE

Y2 - 25 June 2018 through 29 June 2018

ER -