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N.Q. Belzer
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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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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.
Bachelor thesis
(2019)
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Nick Belzer, Buster Bernstein, Jasper Geurtz, Rens Hijdra, Philippe Lammerts, Henk-Jan Wermelink, Christoph Lofi, Otto Visser
Governments require companies to be able to explain where their data is coming from and going to. Our client helps these companies by creating maps of their data landscapes. This is the concept of data lineage. There are various issues that arise in the workflow of figuring out and building data lineage diagrams. Our contributions here are providing a model for what data lineage diagram instances are, and an interactive web application that can be used to visualize and edit these diagrams in an intuitive way. One of the core challenges of this project has been to combine the client's business perspective with our knowledge of computer science. Starting with our research by figuring out the client's use cases, analysing them for their feasibility within the constraints of the project. The team used both Scrum and an agile approach to develop a product that matches the client's expectations and needs throughout the project. The product was tested by adhering to the five metrics defined by the Consortium for IT Software Quality. The final product contains the desired functionality and allows building data lineage diagrams using company data from the client through external APIs. The client is eager to use the product and has provided additional opportunities for the team to work further on the product.
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Governments require companies to be able to explain where their data is coming from and going to. Our client helps these companies by creating maps of their data landscapes. This is the concept of data lineage. There are various issues that arise in the workflow of figuring out and building data lineage diagrams. Our contributions here are providing a model for what data lineage diagram instances are, and an interactive web application that can be used to visualize and edit these diagrams in an intuitive way. One of the core challenges of this project has been to combine the client's business perspective with our knowledge of computer science. Starting with our research by figuring out the client's use cases, analysing them for their feasibility within the constraints of the project. The team used both Scrum and an agile approach to develop a product that matches the client's expectations and needs throughout the project. The product was tested by adhering to the five metrics defined by the Consortium for IT Software Quality. The final product contains the desired functionality and allows building data lineage diagrams using company data from the client through external APIs. The client is eager to use the product and has provided additional opportunities for the team to work further on the product.