Caching for mobile users in edge networks

Master Thesis (2021)
Author(s)

N.Q. Belzer (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

Jan S. Rellermeyer – Mentor (TU Delft - Data-Intensive Systems)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2021 Nick Belzer
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 Nick Belzer
Graduation Date
29-09-2021
Awarding Institution
Delft University of Technology
Programme
Computer Science | Software Technology
Related content

This repository contains the related source code for the dataset retrieval, trace generators, proposed strategies, and experiments in the work.

https://github.com/nbelzer/msc-thesis
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Mobile networks deal with an increasing portion of the IP Traffic due to the significant growth in the number of mobile devices and the accompanied lifestyle. A large fraction of this IP traffic is spent on duplicate transfers for the same resources. Previous work has shown that a Content Delivery Network (CDN) based on edge-nodes can reduce redundant backhaul traffic by storing popular content closer to the user. It also shows that a reduced user population per node, as in edge-based caching systems, can have a significant negative impact on caching performance. This effect is attributed to a reduced view on global content popularity. In this work we first create and evaluate a simulator for resource requests that is used to evaluate different caching strategies in an edge network. Our simulation confirms the findings of previous work and inspire three different caching strategies: Cooperative-LRU, User Profiles, and Hybrid with Federated. These strategies include mobility information to help alleviate the reduced knowledge on content popularity and help nodes work together more efficiently. Our results show that we are successful in decreasing the impact of the reduced population using the Cooperative LRU strategy and Profiles strategy. We then improve upon that performance by using a Hybrid strategy of Federated nodes and one of the mobility strategies.

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