Federated Learning Based Proactive Content Caching in Edge Computing
پنج سال پیش منتشر شده
تعداد بازدید: 352
کد پروژه: 246558
شرح پروژه
Project name
Federated learning-based edge caching and dynamic content popularity estimation
Aim of project
Mobile Edge Computing (MEC) has the capabilities of computing, caching and communication at the network edges that are in close proximity to the end users. Consequently, MEC is able to provide mobile applications, multimedia services as well as to cache popular content files for the mobile subscribers so as to reduce the communication delay and improve the Quality of Experience of users. However, MEC servers face a main challenge of effective content caching due to the limited storage and the dynamic content popularity, which is generally defined as the probability that a specific content is requested at a certain time.
This project aims to investigate effective edge caching scheme based on federated learning algorithms, which is able to learn the dynamic content popularity, and thus updating the cache strategies proactively.
Computing language requires: ( python , matlab )
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