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AI as a Microservice (AIMS) over 5G networks

Lee, GM, Um, T-W and Choi, JK (2018) AI as a Microservice (AIMS) over 5G networks. In: 2018 ITU Kaleidoscope: Machine Learning for a 5G Future (ITU K) . (ITU Kaleidoscope Conference, 26 November 2018 - 28 November 2018, Santa Fe, Argentina).

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As data-driven decision-making services are being infused into Internet of Things (IoT) applications, especially at the 5G networks, Artificial Intelligence (AI) algorithms such as deep learning, reinforcement learning, etc. are being deployed as monolithic application services for autonomous decision processes based on data from IoT devices. However, for latency sensitive IoT applications such as health-monitoring or emergency-response applications, it is inefficient to transmit data to the Cloud data centers for storage and AI based processing. In this article, 5G integrated architecture for intelligent IoT based on the concepts of AI as a microservice (AIMS) is presented. The architecture has been conceived to support the design and development of AI microservices, which can be deployed on federated and integrated 5G networks slices to provide autonomous units of intelligence at the Edge of Things, as opposed to the current monolithic IoT-Cloud services. The proposed 5G based AI system is envisioned as a platform for effective deployment of scalable, robust, and intelligent cross-border IoT applications to provide improved quality of experience in scenarios where real-time processing, ultra-low latency and intelligence are key requirements. Finally, we highlight some challenges to give future research directions.

Item Type: Conference or Workshop Item (Paper)
Additional Information: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords: AI; 5G; Microservice
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science & Mathematics
Publisher: IEEE
Date Deposited: 11 Oct 2018 09:03
Last Modified: 15 May 2024 13:45
DOI or ID number: 10.23919/ITU-WT.2018.8597704
URI: https://researchonline.ljmu.ac.uk/id/eprint/9467
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