Recomendação de conteúdo ciente de recursos como estratégia para cache na borda da rede em sistemas 5G
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2023-10-03
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Universidade Federal de Goiás
Resumo
Recently, the coupling between content caching at the wireless network edge and video
recommendation systems has shown promising results to optimize the cache hit and
improve the user experience. However, the quality of the UE wireless link and the resource
capabilities of the UE are aspects that impact the user experience and that have been
neglected in the literature. In this work, we present a resource-aware optimization model
for the joint task of caching and recommending videos to mobile users. We also present
a heuristic created to solve the problem more quickly. The goal is to maximize the cache
hit ratio and the user QoE (concerning content preferences and video representations)
under the constraints of UE capabilities and the availability of network resources by the
time of the recommendation. We evaluate our proposed model using a video catalog
derived from a real-world video content dataset (from the MovieLens project), real-
world video representations and actual historical records of Channel Quality Indicators
(CQI) representing user mobility. We compare the performance of our proposal with a
state-of-the-art caching and recommendation method unaware of computing and network
resources. Results show that our approach significantly increases the user’s QoE and still
promotes a gain in effective cache hit rate.
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LOUREIRO, A. C. B. Recomendação de conteúdo ciente de recursos como estratégia para cache na borda da rede em sistemas 5G. 2023. 122 f. Tese (Doutorado em Ciência da Computação) - Instituto de Informática, Universidade Federal de Goiás, Goiânia, 2023.