Leveraging network state for software-defined data centre network management

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dc.contributor.advisorSreenan, Cormac J.
dc.contributor.authorSherwin, Jonathanen
dc.contributor.funderMunster Technological University
dc.date.accessioned2023-09-13T13:07:09Z
dc.date.available2023-09-13T13:07:09Z
dc.date.issued2023
dc.date.submitted2023
dc.description.abstractThis work addresses key aspects in the management of a software-defined multi-tenant Data Centre Network (DCN). Software-defined networking (SDN) offers significant potential benefit for many aspects of DCN management – e.g. configuration, monitoring, performance and utilisation, and security – and many researchers have worked, successfully, over the last number of years to show how improvements to these areas could be achieved. The insight that motivated this work is that the focus by researchers and tool vendors has been on managing the current state or desired future state of the DCN. Meanwhile, issues relating to reviewing, analysing and evaluating the past state of a software-defined DCN have been neglected. SDN has been essential for DCNs to meet the requirements of a multi-tenant cloud environment - through automated, dynamic reconfiguration of network devices and services to accommodate tenants arriving, leaving, and modifying their resource requirements via a self-service interface. Consequently, a DCN operator cannot be expected to know the current state of the network, let alone past states, without tools to query the network and provide that information. DCN operators are well served by tools to manage and query the current state of an SDN, but not previous network states and events. The research question addressed in this work is how to record the topological and configuration history of a DCN, present a useful view of that historical record to the DCN operator, and provide the means for the operator to query the historical DCN state. A related question is how to employ SDN itself to improve the performance of a software-defined DCN. Solving these issues is challenging because of the scale of a DCN (potentially scaling to hundreds of switches connecting thousands of devices), the constantly changing configuration of a multi-tenant software-defined DCN, and the duration of months or years over which the history must be recorded, analysed and available for querying. The selected approach takes advantage of the decoupled nature of the control- and data-planes in SDN, to eavesdrop on communications between an SDN controller and switches. Emulated and conceptual models of a DCN have been created from key information extracted from the captured communications. The conceptual model relies on a combination of new and existing ontologies, with an extensible set of concepts and relationships that are the target of complex operator-focussed queries. The contributions of the work are as follows: 1. Accurate reproduction of an emulated copy of a DCN (topology and state) for any time in its history solely from a passively captured log of control-plane messages. 2. The use of snapshots to speed up the reproduction time of an emulated DCN with topology and state for a particular point in time. 3. Use of an ontological approach to creating a temporal and topological model of a DCN, populated solely from a log of control-plane messages, and created for the purpose of answering operator queries. 4. A methodology to develop additional sophisticated queries against the ontological model regarding the historical state of and events on a DCN. 5. A method to improve the veracity of control-plane messages by reducing the latency of interactions between SDN controllers and hardware switches in a DCN.en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationSherwin, J. 2023. Leveraging network state for software-defined data centre network management. PhD Thesis, University College Cork.
dc.identifier.endpage195
dc.identifier.urihttps://hdl.handle.net/10468/14965
dc.language.isoenen
dc.publisherUniversity College Corken
dc.rights© 2023, Jonathan Sherwin.
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectComputer science
dc.subjectNetwork management
dc.subjectSoftware-defined networking
dc.subjectData centre networks
dc.titleLeveraging network state for software-defined data centre network management
dc.typeDoctoral thesisen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhD - Doctor of Philosophyen
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