Billions of devices and sensors ranging from user gadgets to more complex systems with sensing and actuating capabilities, such as power grids or vehicles, from the physical world are getting connected to the Internet. However, the need to operate the scale of heterogeneous devices and sensors while being performance-efficient in real-time is challenging. Typically, the data generated by the devices and sensors are transferred to and processed centrally by services hosted on geographically distant clouds. This is untenable given the communication latency incurred and the ingress bandwidth demand.
A new and disruptive paradigm spear-headed by academics and industry experts is taking shape so that applications can leverage resources located at the edge of the network and along the continuum between the cloud and the edge. These edge resources may be geographically or in the network topology be closer to devices and sensors, such as home router, gateways or more substantial micro data centres. Edge resources may be used to offload selected services from the cloud to accelerate an application or host edge-native applications. The paradigm within which the edge is harnessed is referred to as 'Fog/Edge computing'.
The Fog/Edge computing paradigm is expected to improve the agility of service deployments, make use of opportunistic and cheap computing, and leverage the network latency and bandwidth diversities between these resources. Numerous challenges arise when using edge resources, which requires the re-examination of operating systems, virtualization and containers, and middleware techniques for fabric management. Extensions to current programming and storage models are required and new abstractions that will allow developers to design novel applications that can benefit from massively distributed and data-driven systems need to be developed. Addressing security, privacy and trust of the edge resources is of paramount importance while managing the resources and context for mobile, transient and hardware constrained resources. Lastly, emerging domains like autonomous vehicles and machine/deep learning need to be supported over such platforms.
Sponsor Type:1
General Chairs
Rajkumar Buyya, University of Melbourne, Australia
Yogesh Simmhan, Indian Institute of Science, India
Program Chairs
Blesson Varghese, Queen's University Belfast, UK
Lena Mashayekhy, University of Delaware, USA
Steering Committee
Rajkumar Buyya, University of Melbourne, Australia
Adrian Lebre, INRIA, France
Omer Rana, Cardiff University, UK
Haiying Shen, University of Virginia, USA
Yogesh Simmhan, Indian Institute of Science, India
Anthony Simonet, iExec Blockchain Tech, France
Blesson Varghese, Queen's University Belfast, UK
Massimo Villari, University of Messina, Italy
Publicity Chairs
Luiz F. Bittencourt (South America lead), University of Campinas, Brazil
Antonino Galletta (Europe lead), University of Messina, Italy
Bahman Javadi (Oceania lead), Western Sydney University, Australia
Zhuozhao Li (North America and Asia lead), University of Chicago, USA
Program Committee
David Bermbach, TU Berlin, Germany
Ketan Bhardwaj, Georgia Institute of Technology, USA
Luiz F. Bittencourt, University of Campinas, Brazil
Antonio Brogi, University of Pisa, Italy
Valeria Cardellini, University of Roma "Tor Vergata”, Italy
Lucy Cherkasova, ARM Research, USA
Siobhán Clarke, Trinity College Dublin, Ireland
Saptarshi Debroy, City University of New York, USA
Aaron Ding, TU Delft, Netherlands
Abhishek Dubey, Vanderbilt University, USA
Schahram Dustdar, Vienna University of Technology, Austria
Khalid Elgazzar, Ontario Tech University, Canada
Alex Galis, University College London, UK
Sukhpal Gill, Queen Mary University of London, UK
Aniruddha Gokhale, Vanderbilt University, USA
Daniel Grosu, Wayne State University, USA
Jyotirmoy Karjee, Samsung R&D Institute, India
Hana Khamfroush, University of Kentucky, USA
Chandra Krintz, University of California, Santa Barbara, USA
Adrian Lebre, INRIA, France
Weifa Liang, Australian National University, Australia
Yao Liu, Binghamton University, State University of New York, USA
Sergio Lopes, Polytechnic Institute of Viana do Castelo, Portugal
Tommi Mikkonen, University of Helsinki, Finland
Kwangsung Oh, University of Nebraska Omaha, USA
Claus Pahl, Free University of Bozen-Bolzano, Italy
Panos Patros, University of Waikato, New Zealand
Guillaume Pierre, Rennes 1 University, France
Padmanabhan Pillai, Intel Labs, USA
Radu Prodan, University of Klagenfurt, Austria
Ivan Rodero, Rutgers University, USA
Stefan Schulte, Vienna University of Technology, Austria
Satish Srirama, University of Tartu, Estonia
Adel Nadjaran Toosi, Monash University, Australia
Lin Wang, Vrije Universiteit Amsterdam, Netherlands
Shiqiang Wang, IBM T. J. Watson Research Center, USA
Rich Wolski, University of California, Santa Barbara, USA
Fatos Xhafa, Universitat Politècnica de Catalunya, Spain
Yuanyuan Yang, Stony Brook University, USA
Ming Zhao, Arizona State University, USA
The conference seeks to attract high-quality contributions covering both theory and practice over system software and domain-specific applications related to next-generation distributed systems that use the edge. Some representative topics of interest include, but are not limited to:
Data centers and infrastructures for Fog/Edge computing
Middleware and runtime systems for Fog/Edge infrastructures
Programming models for Fog/Edge computing
Storage and data management platforms for Fog/Edge computing
Scheduling for Fog/Edge infrastructures
Distributed and federated machine learning on Fog/Edge
Performance monitoring and metering of Fog/Edge infrastructures
Legal issues and business aspects of Fog/Edge computing
Security, privacy, trust and provenance issues in Fog/Edge computing
Modelling and simulation of Fog/Edge environments
Novel, latency-sensitive and locality-critical applications of Fog/Edge computing
We invite original manuscripts that have neither been published elsewhere nor are under review at a different venue. The manuscripts should be structured as technical papers, written in English. Authors should submit papers electronically in PDF format and may not exceed 8 letter-size pages in length, including all figures, tables and references. Submissions not conforming to these guidelines or received after the due date may not be reviewed. All manuscripts will be reviewed and judged on originality, technical strength, significance, quality of presentation, and relevance to the conference attendees.
Papers that are accepted for publication may be accepted as REGULAR paper (8 pages) or SHORT paper (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.
05月10日
2021
05月13日
2021
初稿截稿日期
注册截止日期
2018年05月01日 美国
2018 IEEE 2nd International Conference on Fog and Edge Computing2017年05月14日 西班牙 Madrid
2017 IEEE/ACM 1st International Conference on Fog and Edge Computing
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