Quality Reliability Security And Robustness In Heterogeneous Systems
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Quality, Reliability, Security and Robustness in Heterogeneous Systems
This book constitutes the refereed post-conference proceedings of the 13th International Conference on Quality, Reliability, Security and Robustness in Heterogeneous Networks, QShine 2017, held in Dalian, China, in December 2017. The 25 revised full papers were carefully reviewed and selected from 43 submissions. The papers are organized thematically in tracks, starting with mobile and wireless networks, quality and reliability, wireless networking algorithms and protocols, and smart applications.
Quality, Reliability, Security and Robustness in Heterogeneous Systems
This book constitutes the refereed post-conference proceedings of the 17th EAI International Conference on Quality, Reliability, Security and Robustness in Heterogeneous Networks, QShine 2021, held in November 2020. Due to COVID-19 pandemic the conference was held virtually. The 20 revised full papers were carefully reviewed and selected from 43 submissions. The papers are organized thematically in tracks Machine Learning in Distributed Networks; 5G Networks and Security; IoT Security and Lightweight Cryptography; Network Security; and Privacy-preserving Emerging Networked Applications.
Quality, Reliability, Security and Robustness in Heterogeneous Systems
This book constitutes the refereed post-conference proceedings of the 19th EAI International Conference on Quality, Reliability, Security and Robustness in Heterogeneous Networks, QShine 2023, held in October 2023. The 78 full papers included in these proceedings were carefully reviewed and selected from 200 submissions. They are organized in these topical sections: Part I: E-Health networks; transportation networks; reliability and scalability; E-Health networks II; artificial intelligence and machine learning I; networks and applications. Part II: Robustness; Network Security and Privacy; Quality of Service (QoS) and Quality of Experience (QoE); Artificial Intelligence and Machine Learning II; Autonomous Vehicles.