Key Days

Papers due: March 14th, 2022
(FIRM deadline)
Notifications sent: April 22th, 2022
Camera ready paper: May 10th, 2022
Conference date: 30th June - 3rd July, 2022
(*) - Each deadline expires at
23:59:59 EEST

(**)ISCC workshop and co-located event deadlines
can be found on the respective websites.

The conference will be held physically in Rhodes. In case, some presenters will not be allowed to travel due to their institution's or their country's travel restrictions online presentations will be allowed.

  • Co-Design for Edge Intelligence: Perception, Control, Computing

    Autonomous vehicles combine machine learning-based perception with planning and control. Co-design introduces the opportunity for new types of optimizations for perception that range across accuracy, execution time, and power consumption. The requirements on embedded computer vision for autonomy include accuracy, latency, and power consumption. These requirements interact---for example, long latencies can interfere with control performance. This talk will explore the use of co-design to create highly capable and efficient autonomous systems.

    Keynote Speaker
    ▪ Marilyn Wolf, Elmer E. Koch Professor of Engineering Director, School of Computing University of Nebraska -- Lincoln, USA

    Marilyn Wolf is Elmer E. Koch Professor of Engineering and Director of the School of Computing at the University of Nebraska Lincoln. She received her BS, MS, and PhD in electrical engineering from Stanford University in 1980, 1981, and 1984, respectively. She was with AT&T Bell Laboratories from 1984 to 1989. She was on the faculty of Princeton University from 1989 to 2007 and was Farmer Distinguished Chair at Georgia Tech from 2007 to 2019. Her research interests included embedded computing, embedded video and computer vision, and VLSI systems. She has received the IEEE Kirchmayer Graduate Teaching Award, the IEEE Computer Society Goode Memorial Award, the ASEE Terman Award and IEEE Circuits and Systems Society Education Award. She is a Fellow of the IEEE and ACM and an IEEE Computer Society Golden Core member.

  • Federated Learning for Smart City Applications

    Federated learning is a machine learning technique that trains an algorithm across multiple decentralized edge IoT devices without exchanging data samples. This collaborative learning can enhance privacy in many smart city applications. It can help mitigate many of the challenges faced in a centralized learning environment. On the other hand, this can introduce new challenges, such as delay, security and efficacy. With the Internet of Things (IoT) transforming our society by connecting the world, anytime and anywhere, AI can be a great tool to achieve this ultimate objective. This is already adopted to transform the healthcare industry in many ways. However, the use of AI in ubiquitous connections brings with it many challenges that range from providing efficient security to healthcare data to securing complex systems. On the other hand, adversarial AI can slow the adoption of these systems and in turn block such advances. These smart services rely on computation and communication resources. Furthermore, being able to provide adequate services using these complex systems present enormous challenges.

    In this talk, we review the current efforts in using FL to mitigate some of these challenges. Then, we discuss applications on how to efficiently adopt FL in a smart city environment. We showcase our research activities that will contribute to these efforts and advocate possible solutions using AI models. We provide ways on how to manage the available resources intelligently and efficiently in order to offer better living conditions and provide better services. Finally, we discuss some of our research results to support a variety of applications concentrating on the healthcare industry.

    Keynote Speaker
    ▪ Mohsen Guizani, Professor and IEEE Fellow, Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), UAE

    Mohsen Guizani (M’89–SM’99–F’09) received the BS (with distinction), MS and PhD degrees in Electrical and Computer engineering from Syracuse University, Syracuse, NY, USA in 1985, 1987 and 1990, respectively. He is currently a Professor of Machine Learning and the Associate Provost at Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, UAE. Previously, he worked in different institutions in the USA. His research interests include applied machine learning and artificial intelligence, Internet of Things (IoT), intelligent systems, smart city, and cybersecurity. He was elevated to IEEE Fellow in 2009 and was listed as a Clarivate Analytics Highly Cited Researcher in Computer Science in 2019, 2020 and 2021. Dr. Guizani has won several research awards including the “2015 IEEE Communications Society Best Survey Paper Award”, the Best ComSoc Journal Paper Award in 2021 as well five Best Paper Awards from ICC and Globecom Conferences. He is the author of ten books and more than 800 publications. He is also the recipient of the 2017 IEEE Communications Society Wireless Technical Committee (WTC) Recognition Award, the 2018 AdHoc Technical Committee Recognition Award, and the 2019 IEEE Communications and Information Security Technical Recognition (CISTC) Award. He served as the Editor-in-Chief of IEEE Network and is currently serving on the Editorial Boards of many IEEE Transactions and Magazines. He was the Chair of the IEEE Communications Society Wireless Technical Committee and the Chair of the TAOS Technical Committee. He served as the IEEE Computer Society Distinguished Speaker and is currently the IEEE ComSoc Distinguished Lecturer.

  • Leveraging Cloud, Fog and Mist Computing for Time-Critical Applications: Resource Allocation and Scheduling Challenges

    The emergence of the Internet of Things (IoT) contributed to the rapid growth of smart environments, from smart cities and smart transportation to smart healthcare. Due to the massive volume and unprecedented velocity of the generated IoT data, the traditional cloud computing paradigm is no longer practically feasible, as transferring the IoT data to remote datacenters involves significant latency. As a result, new forms of computing have emerged, such as fog and mist computing, which complement and extend the cloud to the edge of the network. These paradigms have been established to solve the problem of transmission latency. As IoT applications are typically time-sensitive, the main goal is to meet their deadlines. Consequently, the utilization of appropriate resource allocation and scheduling strategies for real-time applications in multi-tier environments is crucial. In this keynote, we will present state of the art research driving the development of these computing paradigms. Furthermore, novel techniques addressing the challenges in resource allocation and scheduling in cloud, fog and mist computing infrastructures will be discussed and analyzed.

    Keynote Speaker
    ▪ Helen D. Karatza, Professor Emeritus Department of Informatics Aristotle University of Thessaloniki, Greece

    Helen D. Karatza (senior member of 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, fault tolerance, resource allocation, scheduling algorithms and real-time distributed systems. Dr. Karatza has authored or co-authored over 240 technical papers and book chapters. 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 journal “Simulation Modelling Practice and Theory” (Elsevier), an Editor of “Future Generation Computer Systems” (Elsevier), an Associate Editor of “IEEE Transactions on Services Computing” and an Editor of “Cluster Computing” (Springer). She also served as 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” (Elsevier). She served as Guest Editor of Special Issues in several international journals. More info about her activities and publications can be found at:

  • Post-Quantum Cryptography: What to Expect from this Unprecedented Migration

    Conventional public-key cryptography is expected to be completely broken by large quantum computers. In contrast, Post-quantum Cryptography (PQC) schemes are believed to withstand quantum attacks, and therefore eventually replace conventional schemes. Despite the uncertain timelines regarding quantum computing developments, starting to prepare for this unprecedented migration now is of utmost importance. In this talk, we will be sharing why we consider the PQC migration so special, what deployment strategies tend to lead to a smoother migration, and what lessons can be learned now which can be applied to future crypto migrations.

    Keynote Speaker
    ▪ Rafael Misoczki, Google, California, USA

    Dr. Rafael Misoczki is a cryptographer at Google working on the post-quantum cryptography transition of the company. He's one of the authors of two proposals currently under consideration by NIST in their PQC standardization process (BIKE and Classic McEliece), and the Editor of the ISO/IEC 14888-4 standard on post-quantum stateful hash-based signatures. He is a maintainer of Google's cryptographic library Tink, and was the maintainer of Intel's cryptographic library TinyCrypt. He has 60+ US patents filed, 20+ scientific papers, and his publications have 1,000+ citations. Dr. Misoczki holds a PhD degree in Computer Science from University of Paris, France, with a thesis on efficient post-quantum cryptography constructions.