IEEE CyberSciTech/ PICom/ DASC/ CDBCom 2021

October 25-28, 2021, 2021 - Virtual Conference

Keynote Speakers


DASC Keynote - Understanding and Supporting Humans through Personal Big Data Analysis

Qun Jin, Professor
Department of Human Informatics and Cognitive Sciences, Waseda University, Japan

Abstract: With the innovation of technology and the development of digitalization, a large amount of diverse data that may represent one or more aspects of a person, such as living, working, learning, health, etc., can be collected and accumulated. Such personal big data has the potential to significantly enrich society and make our lives much better than ever. However, personal big data may include sensitive information and individual privacy, which becomes a big challenge for effective use. In this talk, we present our vision on how to understand and support humans through privacy-preserving big data analysis. We discuss important issues in using of personal big data, such as privacy protection and enhancement, data quality assurance and sustainability. We present our latest work on individualized sustainable use of personal big data, privacy-preserving personal analytics and individual modeling, and promising applications to personalized smart services, such as precision healthcare and living support for the elder people.

Biography: Qun Jin is a professor at the Networked Information Systems Laboratory, Department of Human Informatics and Cognitive Sciences, Faculty of Human Sciences, Waseda University, Japan. He has been extensively engaged in research works in the fields of computer science, information systems, and human informatics. His recent research interests cover human-centric ubiquitous computing, behavior and cognitive informatics, big data, personal analytics and individual modeling, cyber security, blockchain, intelligence computing and applications in healthcare, and computing for well-being. He authored or co-authored several monographs and more than 300 refereed papers published in academic journals and international conference proceedings. He served as a general chair, program chair, and keynote speaker for numerous IEEE sponsored international conferences. He served as a guest editor in recent years for IEEE Transactions on Industrial Informatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE Transactions on Computational Social Systems, IEEE Transactions on Emerging Topics in Computing, IEEE MultiMedia, and IEEE Cloud Computing. He is a foreign member of the Engineering Academy of Japan (EAJ). More information can be found at https://researchmap.jp/jinqun/?lang=en.


CBDCom Keynote - Scheduling Real-Time Applications in the Cloud and in the Fog

Helen Karatza, Professor Emeritus
Department of Informatics, Aristotle University of Thessaloniki, Greece

Abstract: For several years cloud computing has been a very popular computing paradigm for the deployment and execution of time-sensitive applications. It provides infrastructure from its virtually infinite pool of resources billed in a pay-as-you-go basis that enables the cloud users to run their applications in a cost-effective way. For efficient cloud performance and quality of service, issues related to resource allocation, application scheduling, timeliness, cost and energy conservation need to be addressed. A particularly challenging issue is to run complex real-time applications in the cloud. Effective scheduling policies should be used ensuring that real-time applications will meet their deadlines as well as the overall quality of service will be improved. Due to the explosive growth of Internet of Things (IoT) paradigm, fog computing has appeared recently as a novel computing model beyond cloud computing to face problems related to large network traffic and communication delay. The majority of the IoT applications are real-time as decisions must be made in a short time. Therefore, new resource allocation techniques and scheduling policies are required for efficient utilization of the resources and for timeliness. Delay-sensitive applications should be assigned to appropriate resources at the fog and cloud layers, based on their communication and computational characteristics. In this talk we will focus on techniques and solutions to address the challenges faced in resource allocation and scheduling of real-time applications in the cloud and in the fog and we will provide future trends in the cloud and fog computing area.

Biography: Helen Karatza (Senior member, IEEE, ACM, SCS) is a Professor Emeritus in the Department of Informatics at the Aristotle University of Thessaloniki, Greece. Dr. Karatza's research interests include Cloud, Fog and Mist Computing, Energy Efficiency, Resource Allocation and Scheduling and Real-time Distributed Systems. Dr. Karatza has authored or co-authored over 240 technical papers and book chapters including six papers that earned best paper awards at international conferences. She served as an elected member of the Board of Directors at Large of the Society for Modeling and Simulation International. She served as Chair and Keynote Speaker in International Conferences. Dr. Karatza is the Editor-in-Chief of the Elsevier Journal “Simulation Modeling Practice and Theory”. She was Editor-in-Chief of “Simulation Transactions of The Society for Modeling and Simulation International”, Associate Editor of “ACM Transactions on Modeling and Computer Simulation” and Senior Associate Editor of the “Journal of Systems and Software” of Elsevier. She is currently an Editorial Board member of “Future Generation Computer Systems”, Elsevier. She served as Guest Editor of Special Issues in International Journals. More info about her activities/publications can be found in: https://users.auth.gr/karatza/.


PICom Keynote - Orchestration of Virtualized Network Services in Edge Computing Environments

Paulo F. Pires, Associate Professor
Department of Computer Science Fluminense Federal University, Brazil

Abstract: The emergence of the Edge Computing paradigm has attracted considerable attention among government organizations, academic institutions, and industry, with each of these segments proposing their own solutions with different approaches in recent years. Rather than replacing cloud computing, the general view is that Edge Computing is a new distributed computing paradigm that will foster a fruitful synergy between the cloud and the edge of the network, creating opportunities for a whole new generation of applications and value-added services for the user. Edge-cloud systems are heavily based on the concept of virtualization, which should provide a clear decoupling between applications and physical infrastructure spanning sensing, processing, storage and communication resources. However, to enable and fully exploit the Edge Computing paradigm and allow an efficient and effective interaction between the edge of the network and the cloud, it is first necessary to extend the provision model and structure of the service-oriented architectures traditionally adopted in Cloud computing for Edge Computing. It is also necessary to provide a holistic solution for infrastructure-level service provision, platform-level resource virtualization, and application-level Quality of Service (QoS) task allocation. To achieve these goals, it is necessary to ensure that each application task to be performed on the system is allocated to the correct components for subsequent processing. In addition, there is a decision-making process, responsible for choosing which tier (edge, cloud or both) is the most suitable to process each request received, considering the application tasks and the QoS requirements to be met, while at the same time optimizing the overall use of available resources.

In this talk, we will discuss the challenges that need to be overcome in resource allocation and orchestration of virtual services in edge computing environments, describe some existing techniques and solutions to solve them, and discuss future trends in this area.

Biography: Paulo F. Pires (DSc COPPE / UFRJ 2002) is an Associate Professor at the at the Fluminense Federal University, Brazil. His main research interests are at the intersection of Software Engineering and Distributed Systems. He has published more than 200 articles from internationally renowned journals, conference articles and book chapters, has eight patents registered with the USPTO (United States) and coordinated several university-industry R&D partnerships projects. Dr. Pires has co-authored two books: “Middleware Solutions for the Internet of Things” (Springer, 2013) and “Resource Management for Internet of Things” (Springer, 2017). He is currently a member of the IEEE TC on Cybermatics, Associate Editor of the IEEE Open Journal of the Communications Society and member of the editorial board of the International Journal of Computer Networks (CSC Journals). Dr. Pires has a CNPq research productivity scholarship since 2010 and is a member of IEEE and the Brazilian Computer Society (SBC).


CyberSciTech Keynote - Misbehaviour Detections for Vehicular Communication Networks

Yi Qian, Ph.D. Professor
Department of Electrical and Computer Engineering University of Nebraska-Lincoln, USA

Abstract: Vehicular networks are susceptible to various attacks from malicious nodes within a network. The collaborative misbehavior detection system can be used to detect these attacks. However, in a collaborative misbehavior detection system, an attacker may send false feedback which affects the detection accuracy. A trust model can be used to stimulate vehicles to send true feedbacks. However, an attacker can take advantage of weak or strong reputation update methods. A dynamic trust can be used to stimulate vehicles to send true feedbacks. In this talk, we present our latest research result on misbehavior detection in 5G based vehicular communication networks, by introducing a deep reinforcement learning based dynamic reputation update. In the proposed method, feedbacks from vehicles are combined in vehicular edge computing (VEC) servers using Dempster-Shafer theory and the results are used to predict the average number of true messages. VEC then uses deep reinforcement learning to determine the optimum reputation update policy to stimulate vehicles to send true feedbacks. In addition, through extensive simulations, we show that the proposed dynamic reputation policy is better in terms of the average number of true feedbacks compared to the existing reputation update policy.

Biography: Yi Qian received a Ph.D. degree in electrical engineering from Clemson University, South Carolina. He is currently a professor in the Department of Electrical and Computer Engineering, University of Nebraska-Lincoln (UNL), USA. Prior to joining UNL, he worked in the telecommunications industry, academia, and government. His research interests include wireless communication networks and systems, and information and communication network security. Prof. Yi Qian is a Fellow of IEEE. He was previously Chair of the IEEE Technical Committee for Communications and Information Security. He was the Technical Program Chair for IEEE International Conference on Communications 2018. He serves on the Editorial Boards of several international journals and magazines, including as the Editor-in-Chief for IEEE Wireless Communications. He was a Distinguished Lecturer for IEEE Vehicular Technology Society. He is currently a Distinguished Lecturer for IEEE Communications Society.