Service Caching

Service caching aims to optimize data placement in distributed networks (like edge computing systems) to minimize latency and maximize resource utilization. Current research focuses on developing sophisticated algorithms, often employing reinforcement learning and deep learning (including graph neural networks), to dynamically adapt caching strategies based on predicted content popularity and network conditions, addressing challenges like limited cache capacity and varying demand. These advancements are crucial for improving the performance and reliability of next-generation wireless networks and other distributed systems, impacting areas such as mobile edge computing and content delivery.