A Study of the Opportunities and Challenges of Using Edge Computing to Accelerate Cloud Applications

dc.contributor.authorQadi, Hala
dc.date.accessioned2025-02-18T19:31:17Z
dc.date.available2025-02-18T19:31:17Z
dc.date.issued2025-02-18
dc.date.submitted2025-02-13
dc.description.abstractI explore the viability of using edge clusters to host latency-sensitive applications and to run services that can improve end-to-end communication performance across both wide area networks (WANs) and 5G environments. The study examines the viability of using edge clusters in three scenarios: accelerating TCP communications through TCP splitting in 5G deployments, hosting an entire application-level service or the latency-sensitive part of an application on an edge cluster, and deploying a TCP splitting service on edge clusters to support WAN communication. I explore these scenarios while varying packet drop rates, communication stacks, congestion control protocols, and TCP buffer sizes. My findings bring new insights about these deployment scenarios. I show that edge computing, especially through TCP splitting, can significantly improve end-to-end communication performance over the classical communication stack. TCP splitting over the 5G communication stack does not bring any benefit and can reduce throughput. This is because of the unique characteristics of the 5G communication stack. Furthermore, over the classical communication stack, TCP splitting brings higher benefit for flows larger than 64 KB. These findings provide valuable insights into how edge clusters can accelerate TCP communication in different network environments and identify high-impact research ideas for future work.
dc.identifier.urihttps://hdl.handle.net/10012/21476
dc.language.isoen
dc.pendingfalse
dc.publisherUniversity of Waterlooen
dc.titleA Study of the Opportunities and Challenges of Using Edge Computing to Accelerate Cloud Applications
dc.typeMaster Thesis
uws-etd.degreeMaster of Mathematics
uws-etd.degree.departmentDavid R. Cheriton School of Computer Science
uws-etd.degree.disciplineComputer Science
uws-etd.degree.grantorUniversity of Waterlooen
uws-etd.embargo.terms0
uws.contributor.advisorAl-Kiswany, Samer
uws.contributor.affiliation1Faculty of Mathematics
uws.peerReviewStatusUnrevieweden
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

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