Abstract: The coverage of network resources is increasingly extensive, and computing resources have likewise gradually become fundamental infrastructures, providing ubiquitous computing services. However, in wide area networks (WANs), the underlying network and computing resources are not closely investigated or co-designed, and there are still problems reflected in slow computing service scheduling, inflexible data distribution, and inefficient data transmission. This paper proposes the architectural design of a computing-aware network (CAN), with the core contribution of introducing the awareness plane to collect, manage, and synthesize computing and network information. In this way, the awareness plane, control plane, and data plane are formed as a closed-loop control system to improve the overall system’s awareness capability, decision-making capability, and data forwarding functionality. To enable the CAN architecture, three key technologies are proposed as follows: computing-aware traffic steering (CATS), elastic broadcast, and wide-area high-throughput transmission. The paper takes artificial intelligence (AI) model training, inference, and offline parameter transmission as examples to show the applicability of CAN and identifies some future research directions.

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