CENet2023
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Submission
Registration
Prospective Challenge
Important Dates
Full paper submission deadline:
June 13, 2023

Acceptance Notification:
June 30, 2023

Registration deadline:
July 14, 2023

Camera-Ready Paper Due: 
July 28, 2023

Conference Date:
November 3-5, 2023
NEWS
The proceedings of CENet2021 have been indexed by EI Compendex! 

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February 14 2018
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The proceedings of CENet2018 have been published by Springer
 
 
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    1. Title:Machine Learning and Optimization for Blockchain based Internet-of-things
    Summary:
    The concepts of Internet of Things (IoT) are providing services across different sectors including agriculture, healthcare, manufacturing, smart cities, smart supply chain, industrial internet and automobile. However, security becomes a major concern in IoT environment, which is important to address before widely deploying the IoT services. Bloackchain is a capable technology that provide transparent, traceable and high level security without being dependent on centralized body. The blockchain technology perfectly fit to the architecture and features of IoT systems. However, the blockchain is still a novel concept and face many challenges specifically related to integration and universal adoption, legal and regulatory status issues, availability, safety, privacy and efficiency. The given challenges motivate us to explore various possible solutions for the secure IoT environment. Machine Learning and Optimization come into play as the leading solution strategies recently. This workshop is concerned with the Machine Learning and Optimization techniques addressing various tasks in blockchain based IoT.
    Keywords:
    Internet of Things, Machine Learning, blockchain
    Chair:
    Dr. Arif Ali Khan, Nanjing University of Aeronautics and Astronautics, China

    Arif Ali Khan is working as an Associate Professor with the College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China. He received B.S. degree in Software Engineering from the University of Science and Technology, Bannu, Pakistan and M.Sc. in Information Technology from Universiti Teknologi Petronas, Malaysia. He obtained Ph.D. degree in Software Engineering from the Department of Computer Science, City University of Hong Kong. He has participated in and managed several empirical software engineering related research projects. Dr Khan has expertise in multi-criteria decision analysis, global software development, process improvement, 3C’s (communication, coordination, control), DevOps, agile software development, requirements change management and evidence-based software engineering. He is professionally active is conducting publication-based research workshops, serving as guest editor in main track software engineering journals and editing research books. He has published over 60 articles in peer reviewed software engineering conferences and journals.


    Dr. Mustafa Misir, Istinye University, Turkey

    Mustafa Misir is an Associate Professor in Computer Engineering at the Istinye University, Turkey. He received his BSc and MSc degrees in Computer Engineering from the Yeditepe University, Turkey in 2007 and 2008, respectively. He earned his PhD degree in Computer Science from KU Leuven, Belgium in 2012 while working in the Combinatorial Optimisation and Decision Support (CODeS) Research Group. He is an expert on Automated Algorithm Design which relates to Machine Learning, Data Science/Analytics and Operations Research. He held many international positions in renowned research institutes including KU Leuven, INRIA, Universite Paris Sud XI, Singapore Management University and University of Freiburg. During this period, he published over 40 papers in international conferences/journals and won several academic awards.



    2. Title:Intelligent Internet of Things Technologies and Applications
    Summary:
    5G networks are widely believed to be the enabler of a broad range of smart applications, such as Smart City, Energy Internet, Smart Agriculture, and so on. The massive Machine Type of Communication (mMTC) of 5G supports up to 1 million device connections per square kilometer, which hence enables high density deployment of a massive number of Internet-of-Things (IoT) devices within a relatively small geographic area. To realize the benefit of 5G in smart applications, Artificial Intelligence (AI) and Edge Computing will play a critical role in implementing and developing the IoT by bringing intelligent computing paradigm and enhancing the quality and performance of the IoT services. It is envisioned that applying AI and Edge Computing technique into mMTC, eMBB and URLLC is a promising approach to solve the scientific and engineering challenges in IoT.
    This Special Workshop is to encourage researchers to present their latest work on how AI and Edge computing work together to address the technology and application challenges of IoT.
    Keywords:
    Internet of Things, Artificial Intelligence, Edge Computing, 5G
    Chair:
    Dr. Sujie Shao, Beijing University of Posts and Telecommunications, China

    Sujie Shao received the Ph.D. degree from Beijing University of Posts and Telecommunication, in 2015, Beijing, China. He is currently a lecturer in State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunication. His research interests include edge computing, Internet of Things, Smart Grids and communication network management.


    A/Prof. Shaoyong Guo, Beijing University of Posts and Telecommunications, China

    Shaoyong Guo received the Ph.D. degree from Beijing University of Posts and Telecommunication, in 2013, Beijing, China. He is currently an associated professor in State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunication. His research interests include Blockchain, Internet of Things, Energy Internet. 



    3. Title:Computing Intelligence driven Mobile Edge Networks
    Summary:
    To address the explosive growth of smart devices, applications, and volume of data traffic, computing and caching capabilities are integrated at the edge of cellular networks compounded with other different types of networks. The new architecture of mobile edge network thus comes into being, which brings network functions and contents close to terminal devices and serves network applications with the integrated communication, computing, and caching resources. In such a compounded network environment, conventional manual work or rule-based paradigms are hard to meet the demand for efficient and effective network operation and management. Computing intelligence is deemed to play a key role in enabling the intelligent management and control of mobile edge networks, by adopting the newly developed computing intelligence approaches, such as deep reinforcement learning, graph neural networks, knowledge graph, etc. However, the potential technologies and practical implementation are still in the very early stage, and there are lots of challenging issues need to be identified and resolved.
    This special Workshop aims to introduce and highlight the latest developments and emerging research in computing intelligence driven mobile edge networks.
    Keywords:
    Computing Intelligence, Mobile Edge Networks,Edge Computing, Internet of Things
    Chair:
    Dr. Fanqin Zhou, Beijing University of Posts and Telecommunications, China

    Fanqin Zhou received the Ph.D. degree from Beijing University of Posts and Telecommunication (BUPT), in 2019, Beijing, China. He is currently a postdoctoral fellow with State Key Laboratory of Networking and Switching Technology in BUPT. His current research interests include intelligent network slicing and resource management of mobile edge networks.



    Dr. Siya XU, Beijing University of Posts and Telecommunications, China.

    Siya Xu, received her Ph.D. degree in communication and information system from Beijing University of Posts and Telecommunications. She is currently a lecturer in State Key Laboratory of Networking and Switching Technology of Beijing University of Posts and Telecommunications. She has published more than 30 EI/SCI index papers in Network Management, AI, SDN, and Edge Computing.



    4. Title:Multidisciplinary and artificial intelligence integration and application

    Summary:
    With the surge of information, communication and electronic equipment in the future, people 's interest in information and data processing in various fields is growing rapidly, so multi-form information and data processing technology is becoming the core part of daily life. In this context, Internet topology analysis has caused a research boom in computer science, physics and mathematical science. Distributed machine learning is also a rapidly developing interdisciplinary field, integrating distributed systems, networks and machine learning technologies. Artificial intelligence and quantum computing will also play a key role in the implementation and development of the Internet, bringing intelligent computing paradigms and improving the quality and performance of Internet services. Developing a common language foundation that can promote interdisciplinary collaboration among researchers, identifying information and information infrastructure needs to support aggregation research. By adopting emerging computational intelligence methods, such as quantum computing, deep reinforcement learning, graph neural networks, and knowledge graphs, seminar activities will promote interdisciplinary dialogue and the rapid development of various information technologies.
    This Workshop aims to present and highlight the latest developments and emerging research in multidisciplinary integration such as quantum computing, artificial intelligence, machine learning and applications of artificial intelligence in materials science.
     
    Keywords:
    Artificial Intelligence, Quantum Computing, Multidisciplinary Integration, Internet

    Chair:
    Dr. Desheng Zheng, Southwest Petroleum University, China

    Desheng Zheng received the Ph.D. degree from University of Electronic Science and Technology of China, in 2014, Chengdu, China. He is currently the master tutor of Southwest Petroleum University. His research interests include Cyberspace Security, Artificial Intelligence, Industrial Internet of Things.




    Prof. Shunkun Yang, Kash Institute of Electronics and Information Industry of China, China

    Shunkun Yang received the master's degree from University of Electronic Science and Technology of China in 2013. He is the executive president of Kash Institute of Electronics and Information Industry of China. His research interests include network security, communication anti-interference and artificial intelligence.



    Dr. Hao Wu, University of Electronic Science and Technology of China, China

    Hao Wu received the Ph.D. degree from University of Science and Technology of China, in 2008, Hefei, China. He is currently an associate professor and master tutor of University of Electronic Science and Technology of China. His research interests include Artificial Intelligence, Quantum Computation, Quantum Machine Learning.



    Dr. QinshengZhu, University of Electronic Science and Technology of China, China

    QinshengZhu received the Ph.D. degree from Sichuan University, in 2008, Sichuan, China. Visiting scholar, Center of Advanced Science and Technology Engineering for Carbon, Case Western Reserve University, USA, in 2013-2014. He is currently an associate professor and master tutor of University of Electronic Science and Technology of China. His research interests include Artificial Intelligence, Quantum information, Quantum Computation, Quantum Machine Learning, Carbon Materials Science.


    5. Title:Information and Data Processing
    Summary:
    We have witnessed fast developments of various information technologies, and many forms of information and data processingtechnologies are becoming core parts of our daily lives. With the proliferation of future information, communication, and electronic devices, there is a fast growing interest in information and data processing. Thisworkshop promotes their transfer into practical applications, for developing intelligent information and data processing for contents, platforms, networks and devices. This workshop aims at addressing advances in research on information and data processing, covering topics ranging from technology issues to applications for information and data processing. This workshop solicits original, unpublished contributions in all aspects of information and data processing. Submitted articles must not be concurrently considered elsewhere for publication. We also encourage authors to submit short papers on the early stages of research or development in progress, which present important new challenges. Position papers on new idea and industry papers are also welcome.
    Keywords:
    Information and Communications Technology, Informaiton processing, Data processing.

    Chair:
    Dr. Yongkai Fan ,Communication University of China, China
    Yongkai Fan received the Bachelor, Master and Ph.D. degrees from Jilin University, Changchun, China, in 2001, 2003, and 2006. From 2006 to 2009, he was an assistant researcher at Tsinghua University, Beijing. He was a visiting scholar in the Department of Computer science and Engineering at Lehigh University in the USA ( 201508-201601 ) and was a visiting scholar in the Department of Computer Science and Engineering at Penn State University in the USA (201602-201608). Dr. Fan is the session chair of Workshop on Big data and machine learning for security in ICCCN 2020, and he is one of the Technical Program Committee in the Joint Workshop on CPS&IoT Security and Privacy in ACM Conference on Computer and Communications Security 2020. His current appointment is an associate professor at the Communication University of China, and his current research interests include theories of software engineering and software security. He has published more than 50 journal/conference papers in journals such as IEEE Transactions on Industrial Informatics, Information Sciences, Future Generation Computer Systems, Computer&Security, and others. His current research interests include theories of software security,AI security and IoT security.

    Prof. Yunfei Yi,Hechi University, China
    Yunfei Yi received the ph.D. degrees in Computer software and theory from Wuhan University, Wuhan,China,2015.He is currently a  professor with the College of Computer and Information Engineering, Hechi University, Yizhou,China. His research interests include natural computation, machine learning, etc.



    Prof. 
    Dong-hong Qin,President of Nanning Branch of China Computer Federation
    Dong-hong Qin received the Ph.D. degrees from Tsinghua University, Beijing, China. He was a visiting scholar in the College of Information and Computer Sciences of University of Massachusetts Amherst in the USA. Prof. Qin is now the President of Nanning Branch of China Computer Federation, and he was the executive chairman of 1stChina-ASEAN Forum on Computer Science, Technology Development and Cooperation in 2019. His current appointment is a professor at the school of artificial intelligence of Guangxi University for Nationalities, and his current research interests include big data, natural language processing, and machine translation on the ASEAN languages. He has published more than 60 journal/conference papers in journals such as IEEE wireless communication and Journal of Internet, and others.
    6. Title:Embedded Computing and Information Security
    Summary:Embedded computing systems are designed to a wide range of competing criteria that have given rise to several different fields. On the one hand, they must perform increasingly complex tasks. On the other hand, embedded systems must meet tight cost, power consumption, and performance constraints. Information security is the practice of preventing unauthorized access, use, disclosure, disruption, modification, inspection, recording or destruction of information. The information or data may take any form, e.g. electronic or physical. Information security’s primary focus is the balanced protection of the confidentiality, integrity and availability of data while maintaining a focus on efficient policy implementation, all without hampering organization productivity. Machine Learning is an idea to learn from examples and experience, without being explicitly programmed. Instead of writing code, you feed data to the generic algorithm, and it builds logic based on the data given.This special Workshop aims to present and highlight the latest developments and emerging research of Embedded Computing, Cryptography Algorithms, Machine Learning with applications in developing all aspects of image, video, music, texture et.al..
    Keywords:
    Embedded Computing; Cryptography; Information Security; Machine Learning; Neural Network;
    Chair:
    Dr.Hui-Huang Zhao, Hengyang Normal University, China
    Dr.Hui-Huang Zhao received his Ph.D. degree in 2010 from XiDian University. He was a Sponsored Researcher in the School of Computer Science and Informatics, Cardiff University. Now he is an Associate Professor in the College of Computer Science and Technology, Hengyang Normal University. His main research interests include Image Processing, Compressive Sensing and Machine Learning.Homepage: http://huihuangzhao.github.io/


    Prof. Bin Fu, University of Texas Rio Grande Valley, USA.
    Prof. Bin Fu received his Ph.D. degree in 1998 from Yale University. He is a Professor in the Department of Computer Science, University of Texas Rio Grande Valley. His main research interests include Algorithms in Networking and Bioinformatics, Computational Complexity Theory.Homepage: https://faculty.utrgv.edu/bin.fu/

    7. Title:Renewable energy Internet
    Summary:Energy is the basis for the survival and development of modern society. In order to cope with the energy crisis, renewable energy such as solar energy, wind energy, and biological energy is widely researched. Renewable energy has inexhaustible, clean and environmentally friendly advantages, while it is geographically dispersed, production discontinuity, random, volatility and uncontrollable.The centralized and unified management of traditional power networks is difficult to adapt to the large-scale use of renewable energy. 
    Energy Internet is the combination of information technology and renewable energy. It comprehensively uses advanced power electronics, information and intelligent management technology to form a large number of distributed energy harvesting devices, storage devices and various types of loads, which provides a feasible technical solution to the problem of efficient use ofrenewable energy. This special Workshop aims to discuss and present the new findings on various key technologies of Energy Internet to gradually evolve the traditional power grid to Energy Internet.
    Keywords:
    Renewable energy; Complex network; Power network; Information technique
    Chair:
    Professor Xi-Zheng Zhang, Hunan Institute of Engineering, China
    Prof. Zhang received his B.s.c, M.s.c, and Ph.D. degreefrom Hunan University in 2000, 2003, and 2010, respectively. Now he is an Professor in the School of Electrical and Information Engineering, Hunan Institute of Engineering. His main research interests include Renewable Energy, Intelligent Optimization,and Control System.




    8. Title:Next-Generation Networking and Internet Security & Applications
    Summary:The next-generation networking and Internet will bring many new challenges and opportunities due to their sensitivity, complexity and advance involved many booming fields, thereby requiring highly adaptive techniques. Following emerging topics are of particular importance to the next generation networking and Internet,such as next-generation communication, data security, Internet of Things, satellite constellation networks, digital economy, e-health, automatic driving, robotics. Furthermore, many salient issues are affecting next-generation networking and Internet, including software-defined network, blockchain, network function virtualization, cloud and fog computing, artificial intelligence, spectrum expansion, resource management, self-organization, energy efficiency operations, mobile edge computing, mobility management, indoor localization, and so on. Networking and Internet have been an indispensable part of daily life and works, however, the next-generation networking and Internet is unprecedentedly changing life and society.
    This workshop solicits unpublished research works related to the latest challenges, technologies, solutions and fundamentals in the broad area of next-generation networking and Internet, including technologies, theories, services, architectures, and protocols.
    Keywords:
    Next-generation networking and Internet, Next-generation communication, Data security, Internet of Things, Satellite constellation networks

    Chair:
    Dr.Zou Zhou, Guilin University of Electronic Technology, China
    Dr. Zou Zhou is an associate professor/senior engineer of Guilin University of Electronic Technology, China. He received the B.S. degree from Huazhong University of Science and Technology, Wuhan, China, in 2002 and the Ph.D. degree at the same university in 2007. From 2008 to 2010, he was a postdoctoral researcher in South China University of Technology,Guangzhou, China. His research interests include distributed swarm intelligence, wireless communication and indoor positioning.

    A/Prof. Fei Zheng, Guilin University of Electronic Technology, China
    Fei Zheng received the Ph.D. degree from Beijing University of Posts and Telecommunication, in 2018, Beijing, China. He is currently an associated professor in Ministry of Education Key Laboratory of Cognitive Radio and Information Processing, Guilin University of Electronic Technology. His research interests include cellularnetworks, satellite constellation networks, powercommunication networks.



     
    To be continued


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