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Multi-Service and Resource Management in Intelligent Edge-Cloud Platform

Submission Deadline: 30 September 2024 View: 82 Submit to Special Issue

Guest Editors

Prof. Young-Sik Jeong, Dongguk University, South Korea
Prof. Laurence T. Yang, St. Francis Xavier University, Canada
Prof. Ji Su Park, Jeonju University, South Korea
Prof. Yi Pan, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China

Summary

With the advent of 5G/6G networks, as services using the Internet of Things (IoT) are gradually spreading and disseminated throughout society and industry, numerous ICT services are emerging. As the flow and movement of data becomes vast due to these services, the amount of traffic and the number of processing tasks increase, causing problems such as network bandwidth problems, bottlenecks, and the risk of overloading the central server (cloud), so that the service cannot be provided immediately. In addition, as it is recently converged with technologies of big data, artificial intelligence, and IoT, new values such as new demand-creating AI convergence projects are created through data analysis, prediction, and autonomous control. Intelligent Edge-Cloud Platforms are being developed to integrate and provide these technologies, and this platform provides intelligent multi-service and resource management.

 

Topics of interest include, but are not limited to:

- Concepts, theory, standardization, and modeling for Intelligence Edge-Cloud Platform

- Resource Management in Intelligent Edge-Cloud Platform

- Multi-Service in Intelligent Edge-Cloud Platform

- AI based algorithm/method for Intelligent Edge-Cloud Platform

- Privacy and Security in Intelligent Edge-Cloud Platform

- Machine learning in Intelligent Edge-Cloud Platform

- Big Data Analysis in Intelligent Edge-Cloud Platform

- New Technology of Internet of Things/Edge/Fog/Cloud computing


Keywords

AI, Multi-Service, Resource Management, Intelligent, Edge-Cloud Platform

Published Papers


  • Open Access

    ARTICLE

    Enhanced Hybrid Equilibrium Strategy in Fog-Cloud Computing Networks with Optimal Task Scheduling

    Muchang Rao, Hang Qin
    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2647-2672, 2024, DOI:10.32604/cmc.2024.050380
    (This article belongs to the Special Issue: Multi-Service and Resource Management in Intelligent Edge-Cloud Platform)
    Abstract More devices in the Intelligent Internet of Things (AIoT) result in an increased number of tasks that require low latency and real-time responsiveness, leading to an increased demand for computational resources. Cloud computing’s low-latency performance issues in AIoT scenarios have led researchers to explore fog computing as a complementary extension. However, the effective allocation of resources for task execution within fog environments, characterized by limitations and heterogeneity in computational resources, remains a formidable challenge. To tackle this challenge, in this study, we integrate fog computing and cloud computing. We begin by establishing a fog-cloud environment… More >

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