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Call for papers
IEEE CCNC 2021 Workshop on
“Traffic Congestion in Beyond 5G/6G Networks" (TCB6GN)
(In conjunction with IEEE CCNC-2021)
9-12 January 2021, Las Vegas, USA
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Scope:
Current ongoing deployment of 5G is regularly exposing the integral limits of the system compared to what promised during the last decade such as Ultra-Reliable Low-Latency Communication (URLLC). This pushes the research community to focus on bringing in new, innovative, relevant technologies keeping the vision of 5G beyond/6G networks intact. Futuristic services such connected Robots, autonomous vehicles, e-health, trustable food supply chain mechanisms, entertainment services broadcasting (Netflix, Amazon Prime) etc. will be highly dependent on instantaneous, virtually limitless wireless connectivity. To bring in and make super-fast connectivity sustainable, a number of research issues such as traffic congestion, URLLC, secure and trustable platforms, interference management, integrating innovative technologies are some of key subjects that need to be touched. In this particular workshop, our focus would be using some core key technologies (Quantum Internet, Blockchain, Machine Learning, Artificial Intelligence etc.) to minimize traffic congestion in the 5G Beyond/6G networks as it is predicted that 10,000 times traffic will Increase in the next decade.
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Congestion Control using Network Slicing, SDN and NFV
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Advanced Machine learning, Deep learning, and AI solutions to improve traffic congestion
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Congestion control techniques in improving user experience in Internet of Things (IoT), Cloud, Edge Computing Networks
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Quality of Service (QoS) issues such as Dynamic Resource Allocation, Spectrum Allocation, Energy Efficiency
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Futuristic paradigms for advanced use cases; adopting blockchain, quantum communication etc.
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Handling Traffic congestion in social networks
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Parameters like Interoperability, heterogeneity, and bandwidth in congested networks
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Unmanned Aerial Vehicle (UAVs)/Internet of Drones with focus on Traffic Congestion
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Emerging cellular architectures for Traffic Congestion Machine learning for smart computing.
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Massive MIMO/Cell free Massive MIMO for Traffic Congestion
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Internet Traffic Offloading Mechanisms using AI, Blockchain, Machine Learning
Keynotes:
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Dr. Dong Sun, Chief Business Strategist, Digital Transformation at Futurewei Technologies, Santa Clara, USA.
Dr. Dong Sun has over 25 years of experience in telecommunications/ICT industry across networking, services and operations, with comprehensive expertise on AI, Big Data, Cloud Computing and Digital Transformation. His current responsibilities include leading business strategy for digital transformation with emphasis on Autonomous Networks/ICT infrastructure & services, driving the overall roadmap of business requirements, architecture and initiatives for strategic collaboration with CSPs and industry partners & alliances. He is active in industry organizations such as TM Forum and ETSI etc on evangelism and standardizations of pertinent topics.
2. TBA