Enterprise Information Systems
Artificial Intelligence Applications in Complex Networks
About the issue:
With the popularity of web-based applications, an increasing number of people are migrating their business processes and daily activities to the web, which form the so called online social networks (e.g., Facebook, Twitter and Instagram). Through online social networks, people can conveniently share their ideas, communicate with each other, make friends with strangers, and so on. Therefore, social networks have become an essential part of human society and unlocked unlimited possibilities in people’s daily lives.
However, the online interactions among people, cyber and things in social networks have been generating an unprecedented volume of social data which create a main source of big data. How to deal with the big and complex social data in an efficient, economical, smart and secure manner is still a fundamental challenge. Recently, machine learning powered Artificial Intelligence (AI) has emerged as one of the key technologies to realize intelligent data analyses and knowledge utilization. Therefore, AI has provided a promising way to extract the valuable knowledge hidden in networks and further improve the network performances. However, the adaptation of AI-based methods is highly demanded to achieve their full potentials in the complex networks.
This special issue focuses on the fundamental theories, algorithms and applications in AI-based smart networks. It aims to share and discuss recent advances and future trends of Artificial Intelligence Applications in Complex Networks, and to bring academic researchers and industry developers together.
Potential topics include but are not limited to the following:
Advanced AI algorithms for complex networks
AI-powered security and privacy protection in networks
Intelligent data preprocess and communications in networks
Complexity measurement and optimization
Smart service discovery, evaluation and recommendation
AI-based routine selection and switch in networks
Self-adaptive and energy-efficient
Trust, reliability and dependability in networks
Multi-modality data integration in networks
New datasets, metrics and benchmarks in networks
AI-powered approach in simplifying complex networks
Complex networks in advanced enterprise and manufacturing systems
Manuscripts Due: 31 October 2021
Final Decision Date: 31 January 2022
(1) Sang-Bing Tsai, School of Business, Wuyi University, Wuyishan, China [Lead Guest Editor]
(2) Lianyong Qi, Qufu Normal University, Rizhao, China
(3) Prof. Xiaochun Cheng, Middlesex University, London, UK
(4) Prof. Fadi Al-Turjman
Research Center for AI and IoT, Near East University, Turkey
Dr. Sang-Bing Tsai
Dr. Sang-Bing Tsai is currently the Professor at University of Electronic Science and Technology of China Zhongshan Institute & Wuyi University, China. He is both Technology Management and Business Management PhD. Dr. Tsai is the Editor-in-Chief for the Journal of Organizational and End User Computing. He also is the Associate Editor for Journal of Global Information Management, as well as serving on the editorial boards of 20 other journals. His recent research interests in Big Data, Computer science and Applied Mathematics. He has well over 150 published peer-reviewed journal articles.
Dr. Lianyong Qi
Dr. Lianyong Qi (EAI Fellow) received his Ph.D degree in Department of Computer Science and Technology from Nanjing University, China, in 2011. In 2010, he visited the Department of Information and Communication Technology, Swinburne University of Technology, Australia. Now, he is a full professor of the School of Computer Science, Qufu Normal University, China. His research interests include big data and privacy-preservation. He has published over 90 research papers (first author / corresponding author) in international journals (e.g., IEEE JSAC, IEEE TITS, IEEE TCC, IEEE TBD, IEEE TII, IEEE TCSS, IEEE TNSE, ACM TOMM, ACM TOSN) and conferences.
Prof. Xiaochun Cheng
He received the BEng Degree in Computer Engineering in 1992, PhD in Computer Science in 1996. He was a Postdoc Research Associate at Sheffield University between 1998 and 2000. He was a Lecturer in Reading University between 2000 and 2005. He has been a Senior Lecturer since 2006 and since 2012 the Computer Science Project Coordinator in Middlesex University. One project was funded with 16 Million Euro. He is a member of the IEEE SMC Technical Committee on Computational Intelligence, IEEE SMC Technical Committee on Intelligent Internet Systems, IEEE Communications Society Communications and Information Security Technical Committee, IEEE Technical Committee on Cloud Computing, BCS AI Specialist Group, BCS Information Security Specialist Group. He contributed for five best conference paper awards. 3 his papers are in the 2020 top 1% of the academic field by Data from Essential Science Indicators. He won 3 times national competitions. He won National Science and Technology Advance Award. He has been invited to be a guest professor by several universities.
Prof. Fadi Al-Turjman
Prof. Dr. Fadi Al-Turjman is a Professor at Near East University, Nicosia. He received his Ph.D. degree in computer science from Queen’s University, Canada, in 2011. He is a leading authority in the areas of smart/cognitive, wireless and mobile networks’ architectures, protocols, deployments, and performance evaluation. His record spans more than 250 publications in journals, conferences, patents, books, and book chapters, in addition to numerous keynotes and plenary talks at flagship venues. He has received several recognitions and best papers’ awards at top international conferences, and led a number of international symposia and workshops in flagship ComSoc conferences. He is serving as the Lead Guest Editor in several journals including the IET Wireless Sensor Systems (WSS), MDPI Sensors, and Wiley Wireless Communications and Mobile Computing (WCMC). He is also the publication chair for the IEEE International Conf. on Local Computer Networks (LCN’18). He is the sole author for 4 recently published books about cognition and wireless sensor networks’ deployments in smart environments with Taylor and Francis, CRC New York (a top tier publisher in the area).