# Dynamic Content Updates in Heterogeneous Wireless Networks

## TL;DR

This paper proposes a learning-based cache refreshment strategy for edge content storage in wireless networks to optimize user satisfaction while managing network costs.

## Contribution

It introduces a novel cache refreshment approach that adapts to user content age tolerance using learning techniques, balancing QoS and network efficiency.

## Key findings

- Enhanced user satisfaction through adaptive cache updates
- Reduced network costs compared to frequent refresh strategies
- Effective learning of user content age preferences

## Abstract

Content storage at the network edge is a promising solution to mitigate the excessive traffic load due to on-demand streaming applications as well as to reduce the streaming delay. To this end, cache-enabled cellular architectures can be utilized to increase the provided quality-of-service (QoS) and to reduce the network cost. However, there are certain issues to be considered in the design of the content storage strategy such that the contents should be refreshed in order to responds user`s expectations. Using a frequent cache refreshment strategy the ratio of satisfied users can be increased at an increasing network cost. In this paper, we introduce a cache refreshment strategy via leveraging learning techniques so that users' tolerance to the age of content is learned and the content is refreshed accordingly.