A review on Caching for minimizing Latency in Edge-Cloud Continuum

The fast growth of latency-sensitive Internet of Things (IoT) applications has made it even more important for cloud-assisted Mobile Edge Computing (MEC) systems to be able to quickly offload tasks and cache services. A lot of research has been done on offloading and caching strategies through joint optimization. However, most of these methods depend on centralized control, static assumptions about service popularity, or computationally intensive learning frameworks, which make them less scalable and adaptable when traffic changes. Furthermore, the coordination of offloading, caching, and service replacement across various temporal scales is inadequately explored in existing literature. This paper provides a thorough review and redefinition of the joint task offloading and service caching problem in cloud-assisted MEC environments, driven by the identified gaps. The proposed solutions are highlighted in future work.