Print Email Facebook Twitter Caching for mobile users in edge networks Title Caching for mobile users in edge networks Author Belzer, Nick (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Rellermeyer, Jan S. (mentor) Degree granting institution Delft University of Technology Programme Computer Science | Software Technology Date 2021-09-29 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. Subject edge computingcachingmobile networksmobility To reference this document use: http://resolver.tudelft.nl/uuid:c27c8d2e-6ba4-406b-b8d3-4fbcd49c480d Bibliographical note https://github.com/nbelzer/msc-thesis This repository contains the related source code for the dataset retrieval, trace generators, proposed strategies, and experiments in the work. Part of collection Student theses Document type master thesis Rights © 2021 Nick Belzer Files PDF msc_thesis_nbelzer_2021_09_27.pdf 7.96 MB Close viewer /islandora/object/uuid:c27c8d2e-6ba4-406b-b8d3-4fbcd49c480d/datastream/OBJ/view