Edge Computing with Optimised Content Caching and User Association in Densely Deployed Heterogeneous Networks

PROJECT TITLE :

Optimized Content Caching and User Association for Edge Computing in Densely Deployed Heterogeneous Networks

ABSTRACT:

It is possible to provide high-speed and low-latency services in next-generation mobile Communication networks by deploying small cell base stations (SBS) under the coverage area of macro base stations (MBS) and caching popular contents at the SBSs in advance. These are both effective ways to provide these services. In this paper, we look into the issues surrounding the edge computing problems of content caching (CC) and user association (UA). In order to reduce the amount of time it takes to download content, an optimization problem that involves both CC and UA has been formulated. We provide evidence that the NP-hardness of the joint CC and UA optimization problem. Then, in order to lessen the amount of time it takes for content to download, we suggest a CC and UA algorithm called JCC-UA. JCC-UA comes equipped with both a smart content caching policy (SCCP) as well as dynamic user association (DUA). The exponential smoothing method is utilized by SCCP in order to predict the popularity of content and to adjust the contents of the cache based on the results of the prediction. The DUA consists of two different methods: the rapid association method (RA) and the delayed association method (DA). The results of the simulations show that the proposed JCC-UA algorithm has the potential to effectively lower the latency of user content downloading and improve the hit rates of contents cached at the BSs in comparison to a number of baseline schemes.

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