Abane, A.
, Battou, A.
, Amlou, A.
and Zhang, T.
(2024),
A Data Collection Platform for Network Management, 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA 2023), Giza, EG, [online], https://doi.org/10.1109/AICCSA59173.2023.10479236, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=956445
(Accessed April 29, 2024)
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A Data Collection Platform for Network Management
Published
Author(s)
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Abstract
Network management relies on extensive monitoring of network state to analyze network behavior, design optimizations, plan upgrades, and conduct troubleshooting. Network monitoring collects various data from network devices through different protocols and interfaces such as NETCONF and Syslog, and from monitoring tools such as Zeek and Osquery. To unify and automate the monitoring workflow across the network, this paper identifies and discusses the data collection requirements for network management, reviews different monitoring approaches, and proposes an efficient data collection platform that addresses the requirements through an extensible and lightweight protocol. The platform design is demonstrated through an adaptive collection of data for network management based on digital twin technology.Conference Dates
December 4-7, 2023
Conference Location
Giza, EG
Conference Title
20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA 2023)
Pub Type
Conferences
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Keywords
network monitoring, network management, publish-subscribe, digital twin network
Citation
Created April 2, 2024, Updated April 13, 2024