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Intelligent Allocation Technologies for All-Scenario KDN Resources

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Key Technologies for On-Demand 6G Network Services

Part of the book series: Wireless Networks ((WN))

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Abstract

The intelligent allocation technology for all-scenario KDN resources focuses on intelligent resource allocation, aiming to address the issue of extracting and utilizing knowledge to allocate all-domain network resources. Building upon the network control knowledge space established in Chap. 5, a knowledge representation system for all-scenario requirements and all-domain resources is developed to facilitate knowledge sharing for resource allocation across various scenarios. Through all-scenario prediction, scheduling, and optimization mechanisms, intelligent, automated allocation, reservation, and distribution of all-domain resources are implemented to enhance the overall performance of 6G networks.

This chapter will introduce the research approach and methods of intelligent allocation technology for all-scenario KDN resources. Firstly, the basic mechanism of knowledge-defined resource allocation will be investigated to establish a research framework for the intelligent allocation technology of all-scenario KDN resources. Subsequently, research will be conducted on various tasks such as traffic awareness, knowledge acquisition, allocation strategy generation, and strategy validation within the context of knowledge-defined resource allocation. This will involve constructing an intelligent control loop to achieve real-time adaptation and dynamic fitting between network resources and intelligent allocation services.

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Authors and Affiliations

  1. The State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China

    Jianxin Liao, Bo He, Jing Wang, Jingyu Wang & Qi Qi

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  1. Jianxin Liao
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Liao, J., He, B., Wang, J., Wang, J., Qi, Q. (2024). Intelligent Allocation Technologies for All-Scenario KDN Resources. In: Key Technologies for On-Demand 6G Network Services. Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-031-70606-6_7

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