Authors - Nguyen Thanh Minh Tam, Mai Nhu Yen, Nguyen Quang Huy, Nguyen Thi Nhung, Nguyen Thi Huyen Chau, Nguyen Hoang Phuong, Dong Van He, Bui Xuan Cuong, Vladik Kreinovich Abstract - The rapid emergence of smart apps in smart environments, industrial automation and cyber-physical systems has demonstrated the intrinsic limitations of conventional design of information and communication technologies. The existing ICT systems are very rigid, centrally controlled and dependent on fixed operation logic and this restricts their dynamism to changing environments and complex system dynamics. Intelligent systems are already urgently in need of architectural paradigms that offer self-education, decentralized intelligence, and autonomous scale-based decision making. The following paper proposes a next-generation Edge-Cloud-AI integrated ICT architecture, which is supposed to service self-learnings and autonomous intelligent systems. The proposed architecture gives a layered intelligence design that utilizes edge level real-time learning, cloud level global optimization, and an autonomy orchestration layer balancing the adaptive behavior in the distributed elements. The architecture enables systems to create operational policies in an autonomous way through the provision of continuous learning feedback and autonomous controls directly within the ICT infrastructure although still be scaled and be reliable. Significant contributions of this work are the definition of a single Edge-Cloud intelligence system, the incorporation of self-learner’s mechanisms along structural layers, and an autonomy-based orchestration model that may be applied to diverse fields of intelligent systems. The proponent architecture is not platform specific and can be applied in a wide range of future intelligent applications that may require resilience, versatility and autonomy.
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