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Artificial intelligence-driven autonomous optical networks: 3S architecture and key technologies

Science China(Information Sciences) 2020年第6期63卷 7-30页

作者： Yuefeng JI Rentao GU Zeyuan YANG Jin LI Hui LI Min ZHANG State Key Laboratory of Information Photonics and Optical Communications School of Information and Communication Engineering Beijing University of Posts and Telecommunications State Key Laboratory of Information Photonics and Optical Communications Institute of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications

In the optical networks, the dynamicity, the complexity and the heterogeneity have dramatically increased owing to the deployment of advanced coherent techniques, and the optical cross-connect technologies and diverse network infrastructures pose great challenges in the optical network management and maintenance for the network operators. In this review, we propose a "3 S" architecture for AI-driven autonomous optical network, which can aid the optical networks operated in "self-aware" of network status, "self-adaptive" of network control, and "self-managed" of network operations. To support these functions, a number of artificial intelligence(AI)-driven techniques have been investigated to improve the flexibility and the reliability from the device aspect to network aspect. Adaptative erbium-doped fiber amplifier(EDFA) controlling is an example for the device aspect, which provides a power self-adaptive capability according to the network *** the link aspect, adaptive fiber nonlinearity compensation, optical monitoring performance and quality of transmission estimation are developed to monitor and alleviate the link-dependent signal impairments in an automatic way. From the network aspect, traffic prediction and network state analysis methods provide the self-awareness, while automatic resource allocation and network fault management powered by AI enhance the self-adaptiveness and self-management capabilities. Benefit from the sufficient network management data,powerful data-mining capability and matured computation units, these AI techniques have great potentials to provide autonomous features for optical networks, including the network resource scheduling and the network customization.

关键词： artificial intelligence optical networks self-aware self-adaptive self-managed

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Health 3.0—The patient-clinician “arabic spring” in healthcare

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Health 2012年第2期4卷 39-45页

作者： Serge Gagnon Laurent Chartier Research and Intervention Centre for Healthy Workplaces (CRISO) McGill University Health Centre Montréal Quebec Canada

A growing number of citizen-patients and clinicians use Communication and self-managed Health Technologies (CSMHT) in their relationship. Doing so, they shift from the current paradigm of dependency to a co-responsibility paradigm in healthcare. Facing the runaway utilization of health services, we need to think “outside the box” to unblock the system. A Health 3.0 development model of governance that position patients as primary members of the clinicians’ team is presented to map this institutional transformation. At the practical level, an MD 3.0 relational model and a Citizen-Patient 3.0 behavioral profile are presented.

关键词： Dependency and Co-Responsibility Paradigm Communication and self-managed Health Technologies Chronic Diseases Runaway Utilization of Health Services Development Matrix of Health 3.0 Governance MD 3.0 Relational Model Citizen-Patient 3.0 Behavioral Profile

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