Important DaysJanuary 21, 2023 (Paper Submission Deadline)
Breakout and Networking SessionDate/Time: TBA
The 7th IEEE International Conference on Fog and Edge Computing (ICFEC 2023) is a leading forum to disseminate and discuss research activities and results on a broad range of topics in the fields of fog and edge computing. ICFEC 2023 will take place in conjunction with The 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2023).
Fog and edge computing have received much attention by both the research community and the industry in recent years, and are today seen as an alternative to the utilization of cloud-based computational resources. Especially, this is the case in scenarios where large amounts of data are produced in distributed settings, e.g., in the Internet of Things (IoT), where data needs to be processed in (near) real time, or where suboptimal network connectivity hampers the upload of very large amounts of data to the cloud. Use cases for fog and edge computing range from smart factories over smart grids to autonomous vehicles, to name just some examples.
While tremendous progress has already been made in the research fields of fog and edge computing, there are still numerous challenges which need to be solved. New abstractions and extensions to current programming and storage models are necessary to allow developers to design novel applications that can benefit from massively distributed fog and edge systems. Addressing security, privacy, and trust is of paramount importance while managing the resources and context of mobile, transient and hardware-constrained resources. Fog and edge computing can also help to process very large amounts of data, both for batch processing and data streams. The integration of novel communication protocols and communication patterns with fog and edge computing also brings both new opportunities and unique challenges. Recently, the utilization of fog and edge resources in order to realize distributed machine learning in the form of federated learning has also gained much traction, since it allows to learn from local data without sharing raw data with any centralized entity.
Download the PDF call for papers here
The conference seeks to attract high-quality contributions covering both theory and practice over systems research and emerging domain-specific applications related to next-generation distributed systems that use the edge and the fog. Some representative topics of interest include, but are not limited to:
We invite original manuscripts that have neither been published elsewhere nor are under review at a different venue. Papers should follow the IEEE template for conference proceedings. Authors should submit papers, written in English, electronically in PDF format and may not exceed 8 letter-size pages in length, including all figures, tables, and references. All manuscripts will be reviewed and judged on originality, technical strength, significance, presentation, and relevance to the conference by at least three reviewers. Papers may be submitted online at https://easychair.org/conferences/?conf=icfec2023
Papers that are accepted for publication may be accepted as REGULAR paper (8 pages) or SHORT papers (5 pages), depending on the reviewer recommendations. Accepted papers will be included in the conference proceedings that will be published through the IEEE Computer Society Conference Publishing Services.
• Scientific Data Division Director, Lawrence Berkeley National Laboratory
• Senior Scientist, Lawrence Berkeley National Laboratory
• Research Affiliate, Berkeley Institute for Data Science, University of California, Berkeley
Dr. Deborah Agarwal is a Senior Scientist and Division Director for the Scientific Data Division, at Lawrence Berkeley National Laboratory (LBNL). The Scientific Data Division (SciData) transforms data-driven discovery and understanding through the development and application of novel data science methods, technologies, and infrastructures with scientific partners. Dr. Agarwal’s current research focuses on developing computational tools to enable scientists to organize and use Earth Science data to address challenges more effectively. She has worked on projects involving carbon flux, watershed understanding, tropical forests, soil carbon, carbon capture, cosmology, particle accelerators, data repositories, and satellite data. She is also active in efforts to broaden diversity in computing research and a member of the Computing Research Association Committee on Widening Participation.
• Director, Google Research India
Dr. Manish Gupta is the Director of Google Research India. He holds an additional appointment as Infosys Foundation Chair Professor at IIIT Bangalore. Previously, Manish has led VideoKen, a video technology startup, and the research centers for Xerox and IBM in India. As a Senior Manager at the IBM T.J. Watson Research Center in Yorktown Heights, New York, Manish led the team developing system software for the Blue Gene/L supercomputer. IBM was awarded a National Medal of Technology and Innovation for Blue Gene by US President Barack Obama in 2009. Manish holds a Ph.D. in Computer Science from the University of Illinois at Urbana Champaign. He has co-authored about 75 papers, with more than 7,000 citations in Google Scholar (and an h-index of 46), and has been granted 19 US patents. While at IBM, Manish received two Outstanding Technical Achievement Awards, an Outstanding Innovation Award and the Lou Gerstner Team Award for Client Excellence. Manish is a Fellow of ACM and the Indian National Academy of Engineering, and a recipient of a Distinguished Alumnus Award from IIT Delhi.
• Professor and Vice-Dean (Research), School of Computing, National University of Singapore
Dr. Bingsheng He is currently a Professor and Vice-Dean (Research) at School of Computing, National University of Singapore. Before that, he was a faculty member in Nanyang Technological University, Singapore (2010-2016), and held a research position in the System Research group of Microsoft Research Asia (2008-2010), where his major research was building high performance cloud computing systems for Microsoft. He got the Bachelor degree in Shanghai Jiao Tong University (1999-2003), and the Ph.D. degree in Hong Kong University of Science & Technology (2003-2008). His current research interests include cloud computing, database systems and high performance computing. He has been a winner for industry faculty awards from Microsoft/NVIDIA/Xilinx/Alibaba. His work also won multiple recognitions as “Best papers” collection or awards in top forums such as SIGMOD 2008, VLDB 2013 (demo), IEEE/ACM ICCAD 2017, PACT 2018, IEEE TPDS 2019, and FPGA 2021. Since 2010, he has (co-)chaired a number of international conferences and workshops, including IEEE CloudCom 2014/2015, BigData Congress 2018 and ICDCS 2020. He has served in editor board of international journals, including IEEE Transactions on Cloud Computing (IEEE TCC), IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS), IEEE Transactions on Knowledge and Data Engineering (TKDE), Springer Journal of Distributed and Parallel Databases (DAPD) and ACM Computing Surveys (CSUR). He is an ACM Distinguished member (class of 2020).
• Professor and Chair, Department of Computer Science, University of Toronto
Dr. Eyal de Lara was awarded his PhD in Electrical and Computer Engineering from Rice University in 2002. Upon graduation, he joined the University of Toronto as an Assistant Professor in the Department of Computer Science. In 2007, he was awarded tenure and promoted to Associate Professor. In 2015, he was promoted to the rank of Professor. He currently serves as the Chair of the department. Professor de Lara’s research lies in the areas of cloud and mobile computing where he has contributed novel algorithms for system virtualization, edge computing, application scaling, indoor localization, mobile security, and continuous mobile sensing. Professor de Lara’s research has had a significant impact in both academia and industry. His research on VM fork, a new cloud computing abstraction, was commercialized by GridCentric, a Toronto based start-up that was acquired by Google. Professor de Lara’s work has been recognized with the EuroSys Test of Time Award, the CACS/AIC Outstanding Young Computer Science Researcher Prize, an NSERC Discovery Accelerator Award, Faculty Awards from IBM and VMware, as well as 3 best paper awards and 2 best paper honorable mentions. Professor de Lara has served as the editor in chief of GetMobile, the flagship publication of ACM SIGMOBILE, and has co-chaired the technical program committees of several conferences including ACM MobiSys and ACM/IEEE SEC, which are respectively the top venues in mobile systems and edge computing. His contributions to the mobile research community have been recognized with the 2020 SIGMOBILE Distinguished Service Award.