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Transformation of Directed Acyclic Graphs into Kubernetes Deployments with Optimized Latency / Transformation av riktade acykliska grafer till Kubernetes-distributioner med optimerad latens

In telecommunications, there is currently a lot of work being done to migrate to the cloud, and a lot of specialized hardware is being exchanged for virtualized solutions. One important part of telecommunication networks that is yet to be moved to the cloud is known as the base-band unit, which sits between the antennas and the core network. The base-band unit has very strict latency requirements, making it unsuitable for out-of-the-box cloud solutions. Ericsson is therefore investigating if cloud solutions can be customized in such a way that base-band unit functionality can be virtualized as well. One such customization is to describe the functionality of a base-band unit using a directed acyclic graph (DAG), and deploy it to a cloud environment using Kubernetes. This thesis sets out to take applications represented using a DAG and deploy it using Kubernetes in such a way that the network latency is reduced when compared to the deployment generated by the default Kubernetes scheduler. The problem of placing the applications onto the available hardware resources was formulated as an integer linear programming problem. The problem was then implemented using Pyomo and solved with the open-source solver GLPK to obtain an optimized placement. This placement was then used to generate a configuration file that could be used to deploy the applications using Kubernetes. A mock application was developed in order to evaluate the optimized placement. The evaluation carried out in this thesis shows that the optimized placement obtained from the solution could improve the average round-trip latency of applications represented using a DAG by up to 30% when compared to the default Kubernetes scheduler.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-189979
Date January 2022
CreatorsAlmgren, Robert, Lidekrans, Robin
PublisherLinköpings universitet, Institutionen för datavetenskap
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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