… Then, we propose a graph attention-based multi-agent reinforcement learning (GatMARL) …
and service caching strategies in the DITEN. The GatMARL employs a graph attention-based …

… task offloading, service caching, and transmit … a graph attention based multi-agent deep
deterministic policy gradient (GAT-MADDPG) algorithm, in which a multi-headed graph attention …

… graph. In this paper, to maximize the cache hit rate, we leverage an effective dynamic graph
… graph. Furthermore, in order to have deeper insights into the dynamics within the evolving …

… spatial-temporal graph attention neural network caching strategy, … Graph Attention Neural
Network (GAT) caching strategy to extract spatial-temporal characteristics for edge caching …

… design a multi-head attention based popularity prediction caching strategy in MeSoCCN.
First… cache space at the edge of the network. Second, we propose a multi-head attention based …

… proposed a distributed task offloading and data caching method to reduce the service
latency and improve the storage utilization of edge servers. This method greatly reduces the …

… Graph attention network is adopted to compute the interaction between services for learning
representation of services. … 4) Service Representation Learning: A graph attention network is …

… service providing framework for ICTS is designed. Then, a graph attention network (GAT)
based service … (A3C) based service caching scheme are presented. Besides, the generated …

… to providing various services to meet distinct requirements over … satisfy the fluctuations of
distinct service requirements. In this paper, … Then, we leverage graph attention network (GAT) to …

… limited cache resources, we utilize a multi-head attention technique … • We model the
heterogeneous edge caching issue as the … caching strategy by considering the multi-head …