Edge Caching Based on Deep Reinforcement Learning and Transfer Learning

arXiv:2402.14576v1 Announce Type: cross
Abstract: This paper addresses the escalating challenge of redundant data transmission in networks. The surge in traffic has strained backhaul links and backbone networks, prompting the exploration of caching solutions at the edge router. Existing work primarily relies on Markov Decision Processes (MDP) for caching issues, assuming fixed-time interval decisions; however, real-world scenarios involve random request arrivals, and despite the critical role of various file characteristics in determining an optimal caching policy, none of the related …

abstract arxiv caching challenge cs.lg cs.ni cs.sy data decision edge eess.sy exploration markov networks paper processes prompting reinforcement reinforcement learning solutions the edge traffic transfer transfer learning type work