Next generation Software-defined Networks (SDN)
aim at deeply programmable switches which can be leveraged
by SDN controllers to offload self-contained, logically persistent
tasks. One such task is flow and network monitoring, specifically,
fault detection and loss estimation, which is essential for SDN
applications that provide quality of service guarantees under
network dynamics. In this work, we devise, implement, and
evaluate fault detection and loss estimation techniques built upon
tasks devolved to SDN switches. Subsequently, we contribute (i)
an analysis and empirical evaluation of the benefits and costs
of different packet loss estimators depending on the network
conditions; (ii) a case study showing how an adaptive monitoring
framework which flexibly exchanges the estimation techniques
would retain a thoroughly good fidelity while optimizing the
monitoring costs.
%0 Conference Paper
%1 hark2017towards
%A Hark, Rhaban
%A Richerzhagen, Nils
%A Richerzhagen, Björn
%A Rizk, Amr
%A Steinmetz, Ralf
%B 16th IFIP Networking 2017 Conference (NETWORKING'17)
%D 2017
%I IEEE
%K myown sendate sendate-ger sendate-planets
%P 1-9
%T Towards an Adaptive Selection of Loss Estimation Techniques in Software-defined Networks
%X Next generation Software-defined Networks (SDN)
aim at deeply programmable switches which can be leveraged
by SDN controllers to offload self-contained, logically persistent
tasks. One such task is flow and network monitoring, specifically,
fault detection and loss estimation, which is essential for SDN
applications that provide quality of service guarantees under
network dynamics. In this work, we devise, implement, and
evaluate fault detection and loss estimation techniques built upon
tasks devolved to SDN switches. Subsequently, we contribute (i)
an analysis and empirical evaluation of the benefits and costs
of different packet loss estimators depending on the network
conditions; (ii) a case study showing how an adaptive monitoring
framework which flexibly exchanges the estimation techniques
would retain a thoroughly good fidelity while optimizing the
monitoring costs.
%@ 978-3-901882-94-4
@inproceedings{hark2017towards,
abstract = {Next generation Software-defined Networks (SDN)
aim at deeply programmable switches which can be leveraged
by SDN controllers to offload self-contained, logically persistent
tasks. One such task is flow and network monitoring, specifically,
fault detection and loss estimation, which is essential for SDN
applications that provide quality of service guarantees under
network dynamics. In this work, we devise, implement, and
evaluate fault detection and loss estimation techniques built upon
tasks devolved to SDN switches. Subsequently, we contribute (i)
an analysis and empirical evaluation of the benefits and costs
of different packet loss estimators depending on the network
conditions; (ii) a case study showing how an adaptive monitoring
framework which flexibly exchanges the estimation techniques
would retain a thoroughly good fidelity while optimizing the
monitoring costs.},
added-at = {2017-10-09T11:31:51.000+0200},
author = {Hark, Rhaban and Richerzhagen, Nils and Richerzhagen, Björn and Rizk, Amr and Steinmetz, Ralf},
biburl = {https://www.bibsonomy.org/bibtex/28e1d065c151978086e30d579afb8f8b5/rhabanhark},
booktitle = {16th IFIP Networking 2017 Conference (NETWORKING'17)},
interhash = {743f6d5e89b3259855200f3a85b94ac4},
intrahash = {8e1d065c151978086e30d579afb8f8b5},
isbn = {978-3-901882-94-4},
keywords = {myown sendate sendate-ger sendate-planets},
language = {english},
month = {June},
organization = {IFIP},
pages = {1-9},
publisher = {IEEE},
timestamp = {2018-04-17T12:49:50.000+0200},
title = {Towards an Adaptive Selection of Loss Estimation Techniques in Software-defined Networks},
year = 2017
}