Date of Award

2024

Document Type

Thesis

Degree Name

Master of Science in Engineering (MSE)

Department

Electrical and Computer Engineering

Committee Chair

David Coe

Committee Member

Aleksandar Milenkovic

Committee Member

Earl Wells

Research Advisor

David Coe

Subject(s)

Web servers, Internet of things, Cloud computing, Raspberry Pi (Computer)

Abstract

As the world’s reliance on the internet continues to grow, so does the need for cloud-based computing solutions. These solutions offer a degree of flexibility, scalability, and reliability that traditional computing methods cannot provide. This thesis focuses on characterizing a web server deployed in a lightweight Kubernetes cluster hosted across three Raspberry Pi 4 minicomputers. Characterization metrics include the transfer rate of data from the web server as well as the CPU utilization and power consumption of the Raspberry Pi devices when under load. The background on cloud-based technology is introduced and the tools used in the thesis research are discussed. Experimental methods are then detailed and the results for several cluster-based deployments of the web server are presented. Finally, these results are compared to those obtained for an identical web server hosted locally on a Raspberry Pi device external to the Kubernetes cluster.

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