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IntOpt: In-Band Network Telemetry Optimization for NFV Service Chain Monitoring
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Disco, Computer Networking)ORCID iD: 0000-0002-8925-6859
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Disco, Computer Networking)ORCID iD: 0000-0002-9446-8143
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Disco, Computer Networking)ORCID iD: 0000-0001-7358-8675
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Disco, Computer Networking)ORCID iD: 0000-0002-6101-4305
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2019 (English)In: 2019 IEEE International Conference on Communications (ICC) Próceedings, 2019Conference paper, Published paper (Refereed)
Abstract [en]

Managing and scaling virtual network function(VNF) service chains require the collection and analysis ofnetwork statistics and states in real time. Existing networkfunction virtualization (NFV) monitoring frameworks either donot have the capabilities to express the range of telemetryitems needed to perform management or do not scale tolarge traffic volumes and rates. We present IntOpt, a scalableand expressive telemetry system designed for flexible VNFservice chain network monitoring using active probing. IntOptallows to specify monitoring requirements for individual servicechain, which are mapped to telemetry item collection jobsthat fetch the required telemetry items from P4 (programmingprotocol-independent packet processors) programmable dataplaneelements. In our approach, the SDN controller creates theminimal number of monitoring flows to monitor the deployedservice chains as per their telemetry demands in the network.We propose a simulated annealing based random greedy metaheuristic(SARG) to minimize the overhead due to activeprobing and collection of telemetry items. Using P4-FPGA, webenchmark the overhead for telemetry collection and compareour simulated annealing based approach with a na¨ıve approachwhile optimally deploying telemetry collection probes. Ournumerical evaluation shows that the proposed approach canreduce the monitoring overhead by 39% and the total delays by57%. Such optimization may as well enable existing expressivemonitoring frameworks to scale for larger real-time networks.

Place, publisher, year, edition, pages
2019.
Keywords [en]
In-band Network Telemetry, Monitoring, P4, Service Function Chain, Software Defined Networks
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-74631DOI: 10.1109/ICC.2019.8761722ISBN: 978-1-5386-8089-6 (print)ISBN: 978-1-5386-8088-9 (electronic)OAI: oai:DiVA.org:kau-74631DiVA, id: diva2:1348380
Conference
IEEE ICC 2019: IEEE International Conference on Communications 2019 Shanghai, China 20-24 May
Projects
HITS, 4707
Funder
Knowledge FoundationAvailable from: 2019-09-04 Created: 2019-09-04 Last updated: 2019-09-19Bibliographically approved

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Bhamare, DevalKassler, AndreasVestin, JonathanKhoshkholghi, Mohammad AliTaheri, Javid
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CiteExportLink to record
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