面向自主计算的存算传融合架构及技术挑战

Caching, computing, and communication are separately organized under the conventional cloud and edge computing. Specifically, end devices are responsible for specifying specific computation and associated storage nodes, while the network mainly provides transmission paths between these nodes without awareness of the computing tasks. In this regard, heterogeneous caching-computing platforms cannot discover and coordinate available resources, leading to prolonged or even interrupted task execution when dealing with dynamic network topologies and node failures. To address these challenges, we propose a caching-computing-communication integrated network architecture for automatic computing. The main design aspects include an integrated yet differentiated control plane to manage caching, computing, and communication resources, and a data plane supporting formalized computation task routing and scheduling. Furthermore, we explore methods for multi-dimensional resource state detection, joint task scheduling, and coordinated service deployment to enable efficient automatic computing that dynamically adapts to task demands and environmental changes. The related open research issues are also discussed.