Literature Database Entry
jo2023intelligent
Min He Jo, "Intelligent Container Migrations in an Urban Vehicular Virtual Edge," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), July 2023. (Advisor: Gurjashan Singh Pannu; Referees: Falko Dressler and Thomas Sikora)
Abstract
Edge computing has brought computational capabilities closer to the network edge with better latency. However, edge servers’ cost and limited availability have motivated alternative solutions, such as vehicular virtual edge computing, also known as v-edge. V-edge leverages a group of cars as an edge server within a specific geographic area. In highly mobile environments, smooth service delivery relies on cost-effective container migration to address the loss of services when cars exit the v-edge boundary. In order to address this challenge, a novel container migration protocol based on single-agent Reinforcement Learning (RL) is proposed, considering multiple optimization goals, including migration success rate, overhead minimization, and workload balance. Experimental results demonstrate the superior performance of RL compared to fixed algorithms under certain conditions, achieving high migration success rates, minimizing overhead, and achieving uniform workload distributions. The results validate the effectiveness of RL in dynamic distributed systems, particularly in v-edge environments. In summary, the thesis demonstrates the value of RL-based approaches in optimizing container migration in vehicular v-edge environments and provides insights into its limitations and potential for further exploration.
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Min He Jo
BibTeX reference
@phdthesis{jo2023intelligent,
author = {Jo, Min He},
title = {{Intelligent Container Migrations in an Urban Vehicular Virtual Edge}},
advisor = {Pannu, Gurjashan Singh},
institution = {School of Electrical Engineering and Computer Science (EECS)},
location = {Berlin, Germany},
month = {7},
referee = {Dressler, Falko and Sikora, Thomas},
school = {TU Berlin (TUB)},
type = {Master's Thesis},
year = {2023},
}
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