Edge Computing – EDGE 2023 [[electronic resource] ] : 7th International Conference, Held as Part of the Services Conference Federation, SCF 2023 Shenzhen, China, December 17-18, 2023, Proceedings / / edited by Jun Feng, Frank Jiang, Min Luo, Liang-Jie Zhang

• Autore: Feng Jun
• Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
• Edizione: 1st ed. 2024.
• Descrizione fisica: 1 online resource (104 pages)
• Disciplina: 004.6
• Soggetto topico: Computer networks; Computer engineering; Software engineering; Computer Communication Networks; Computer Engineering and Networks; Software Engineering
• Altri autori: JiangFrank LuoMin ZhangLiang-Jie
• Nota di contenuto: Research and Application of Low Voltage Distributed Power Supply Control System -- Optimized Edge-cCCN Based Model for the Detection of DDoS Attack in IoT Environment -- RuCIL: Enabling Privacy-Enhanced Edge Computing for Federated Learning -- Designing Blended Learning Activities in the Era of Artificial Intelligence -- Data Standard Construction -- Construction and Application of Enterprise Data Assets based on Data Label System -- Secure and Fast Query Approach for High-precision Multi-dimensional Satellite Remote Sensing Data -- Data Operation and Management Practices in Ping An Group. .
• Sommario/riassunto: This book constitutes the refereed proceedings of the 7th International Conference on Edge Computing, EDGE 2023, held in Shenzhen, China, during December 17–18, 2023. The 8 full papers in this book were carefully reviewed and selected from 14 submissions. They were organized in topical sections as follows: Practice of Edge Computing, identify emerging research topics, and define the future of Edge Computing.
• Titolo autorizzato: Edge Computing – EDGE 2023
• ISBN: 3-031-51826-8
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910805581703321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Computer Science, . 1611-3349 ; ; 14205