Business differentiation-aware intelligent converged communication orchestration technology for distribution network

Qing Liu; Wei Tang; Xu Liu; Ji Shi; Linyu Peng; Guanghui Zhang; Xinyang Liu

doi:10.1117/12.2679571

16 June 2023 Business differentiation-aware intelligent converged communication orchestration technology for distribution network

Qing Liu, Wei Tang, Xu Liu, Ji Shi, Linyu Peng, Guanghui Zhang, Xinyang Liu

Author Affiliations +

Proceedings Volume 12702, International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023); 127021U (2023) https://doi.org/10.1117/12.2679571
Event: International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023), 2023, Changsha, China

Abstract

With massive access of distributed photovoltaic, distributed energy storage station, and other equipment, the number of power distribution network devices growth rapidly. To satisfy differentiated QoS requirements of different businesses, distribution network communication needs to choose the appropriate communication method according to the characteristics of different devices business. Hence, Business differentiation-aware intelligent converged communication orchestration technology for distribution network under uncertain global state information was proposed in this paper, which dynamically learning communication orchestration strategy by adopting historical information to perceive business differentiation to maximize the utility function of the devices. Finally, simulation results demonstrates that compare with two existing algorithms, the proposed algorithm has superior performances.

Citation Download Citation

Qing Liu, Wei Tang, Xu Liu, Ji Shi, Linyu Peng, Guanghui Zhang, and Xinyang Liu "Business differentiation-aware intelligent converged communication orchestration technology for distribution network", Proc. SPIE 12702, International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023), 127021U (16 June 2023); https://doi.org/10.1117/12.2679571

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