Research Article
Intelligent Logistics Service Quality Assurance Mechanism Based on Federated Collaborative Cache in 5G+ Edge Computing Environment
@INPROCEEDINGS{10.1007/978-3-031-58053-6_11, author={Yiwen Liu and Jinrong Fu and Zikai Zhao and Yahui Yang and Ling Peng and Taiguo Qu and Tao Feng}, title={Intelligent Logistics Service Quality Assurance Mechanism Based on Federated Collaborative Cache in 5G+ Edge Computing Environment}, proceedings={Wireless Internet. 16th EAI International Conference, WiCON 2023, Athens, Greece, December 15-16, 2023, Proceedings}, proceedings_a={WICON}, year={2024}, month={5}, keywords={5G+ Edge computing Federated cooperative cache Intelligent logistics Service quality}, doi={10.1007/978-3-031-58053-6_11} }- Yiwen Liu
Jinrong Fu
Zikai Zhao
Yahui Yang
Ling Peng
Taiguo Qu
Tao Feng
Year: 2024
Intelligent Logistics Service Quality Assurance Mechanism Based on Federated Collaborative Cache in 5G+ Edge Computing Environment
WICON
Springer
DOI: 10.1007/978-3-031-58053-6_11
Abstract
Aiming at the problem of quality assurance of intelligent logistics service in 5G+ edge computing environment, this paper proposes a mechanism based on federated cooperative cache, which aims to utilize the computing and storage resources of edge nodes to realize rapid processing and sharing of logistics data and improve the efficiency and reliability of logistics services. This paper first analyzes the characteristics and challenges of intelligent logistics services under 5G+ edge computing environment, and then introduces the concept and principle of federated cooperative cache, as well as its application scenarios and advantages in intelligent logistics services. Then, this paper designs an intelligent logistics service quality assurance mechanism based on federated cooperative cache, including five modules such as data partitioning, data transmission, data fusion, data access and data update, and gives the corresponding algorithms and processes. Finally, this paper verifies the effectiveness and performance of the proposed mechanism through simulation experiments. Compared with the traditional centralized cache and distributed cache, the proposed mechanism can reduce the data transmission delay, improve the data hit rate and data consistency, so as to ensure the quality of intelligent logistics services. In the future, the federated collaborative cache mechanism can be further optimized to consider the needs of multiple scenarios. And explore the application potential of other areas to drive the continuous development and innovation of intelligent logistics services.
