Abstract The deployment of artificial intelligence (AI) technology in various emerging network applications has spawned a large number of computing tasks, which require dynamic collaboration of multi-dimensional resources from the perspective of communication and computing to meet service requirements such as ultra-low latency, ultra-high reliability, and ultra-fast response. In this paper, we introduce a Computing Integration Networking (CIN) architecture, which built to integrate ubiquitous heterogeneous resources in the Internet into a distributed pool, enabling CIN paradigm to fully utilize all available heterogeneous resources and provide efficient customized services evolving both communication and computation. Owing to network function virtualization (NFV) technology, computing services can be implemented as service chains, which are composed of ordered virtual network functions. We then design a service chain-driven CIN architecture with “three layers and three domains” characteristics, which consists of generalized service layer, mapping adaption layer and converged network layer. The designed architecture enables the adaptability for users, flexibility for CIN, and profitability for providers. Furthermore, we outline key technologies such as measurement and modeling of multi-dimensional heterogeneous resources, fine-grained multi-dimensional awareness, multi-dimensional identification networking and heterogeneous resources allocation. In addition, we formulate the heterogeneous resource joint optimization problem and verify the effectiveness of the designed scheme. Furthermore, we explore open issues based on our review and indicate potential research trends of the new computing paradigm.
Chen et al. (Thu,) studied this question.