Date of Award

6-14-2021

Document Type

Thesis

Publisher

Santa Clara : Santa Clara University, 2021.

Department

Computer Science and Engineering

First Advisor

Behnam Dezfouli

Abstract

Considering the limited resources of edge devices, it is essential to monitor their current resource utilization and device resource allocation strategies that assign containers to edge and cloud nodes based on their priority. Edge containers may need to be migrated to a cloud platform to reduce the load of edge devices and allow for running missions critical applications. In this case, we proposed a prioritization method to exchange containers between the edge and cloud, while trying to assign delay-sensitive containers to edge nodes. We evaluate the performance of running Docker container management systems on resource-constrained machines such as Raspberry Pi, and propose methods to reduce the overhead of management and migration depending on the workload type.

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