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.
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:
Download the PDF call for papers here
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. Papers should follow the IEEE format template for conference proceedings available here. 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.
Accepted papers will be included in the conference proceedings that will be published through the IEEE Computer Society Conference Publishing Services.
The acceptance rate of regular papers this year is 17%.
Authors of accepted papers must submit the camera-ready papers here by 26 March 2021.
Regular papers may not exceed 10 pages (at no additional costs) for the camera-ready version.
Short papers may not exceed 5 pages (at no additional costs) for the camera-ready version.
Authors of accepted papers should register here by 25 March 2021.
Further information on the registration fee is available here and other notes are available here.
Please note the conference will be held as an online event this year. To attend the online event register for free here.
Papers due: 24 January 2021 23:59 GMT
Author notifications: 27 February 2021
Author registration due: 25 March 2021
Camera Ready due: 26 March 2021
Speaker: Dr Humberto J. La Roche, Cisco
Title: 5G Architecture and Emergence of the Edge
Abstract: Among the many areas of impact 5G will have is the nature of “edge”. As recently as ten years ago, with LTE and prior wireless generations, it was common to build networks with highly centralized service nodes. With LTE, we expect the traditional network morphology to flip on its heels with the emergence of a top-heavy “edge”. In this presentation, we discuss the interpretation and causes of this inversion and highlight some of the most immediate consequences.
Biography: Humberto J. La Roche is Principal Engineer in Cisco’s Mass-scale Infrastructure Group where he is responsible for 5G solution architecture. In his career spanning over twenty-five-year in telecom, he has been responsible for LTE systems engineering, product management of IMS and wireless softswitch products, product planning of optical networking and broadband access products, and transport network design. He is listed as author in over eleven technical papers and as inventor on over twenty patents. Humberto holds a PhD degree in Physics from the University of Texas at Austin.
Free registration to attend the online event - Click here.
Priority-enabled Load Balancing for Dispersed Computing
Aaron Paulos (Raytheon BBN Technologies, USA), Soura Dasgupta (University of Iowa, USA), Jacob Beal (Raytheon BBN Technologies, USA), Yuangiu Mo (University of Iowa, USA), Jon Schewe, Alexander Wald, Partha Pal, Richard Schantz (Raytheon BBN Technologies, USA), J. Bryan Lyles (University of Tennessee Knoxville, USA)
Multilayer Resource-aware Partitioning for Fog Application Placement
Zahra Najafabadi Samani, Nishant Saurabh, Radu Prodan (University of Klagenfurt, Austria)
CHANGE: Delay-Aware Service Function Chain Orchestration at the Edge
Lei Wang (University of Calgary, Canada), Mahdi Dolati (University of Tehran, Iran), Majid Ghaderi (University of Calgary, Canada)
LEAF: Simulating Large Energy-Aware Fog Computing Environments
Philipp Wiesner, Lauritz Thamsen (Technische Universität Berlin, Germany)
AVEC: Accelerator Virtualization in Cloud-Edge Computing for Deep Learning Libraries
Jason Kennedy, Blesson Varghese, Carlos Reano (Queen’s University Belfast, UK)
Reducing the Mission Time of Drone Applications through Location-Aware Edge Computing
Theodoros Kasidakis, Giorgos Polychronis, Manos Koutsoubelias, Spyros Lalis (University of Thessaly, Greece)
TOD: Transprecise Object Detection to Maximise Real-Time Accuracy on the Edge
JunKyu Lee, Blesson Varghese, Roger Woods, Hans Vandierendonck (Queen’s University Belfast, UK)
Mapping IoT Applications on the Edge to Cloud Continuum with a Filter Stream Model
Shuangsheng Lou (Ohio State University, USA), Gagan Agrawal (Augusta University, USA)
PA-offload: Performability-aware Adaptive Fog Offloading for Drone Image Processing
Fumio Machida (University of Tsukuba, Japan), Ermeson Andrade (Federal Rural University of Pernambuco, Brazil)
A Privacy Preserving System for AI-assisted Video Analytics
Clemens Lachner, Thomas Rausch, Schahram Dustdar (Vienna University of Technology, Austria)
Distributed Resource Management Across the Edge-to-Cloud Continuum
Andre Luckow (Ludwig Maximilian University of Munich, Germany), Kartik Rattan, Shantenu Jha (Rutgers University, USA)
Performance Evaluation of Some Adaptive Task Allocation Algorithms for Fog Networks
Ioanna Stypsanelli, Olivier Brun, Balakrishna Prabhu (French National Centre for Scientific Research, France)
Deep-Edge: An Efficient Framework for Deep Learning Model Update on Heterogeneous Edge
Anirban Bhattacharjee, Ajay Chhokra, Hongyang Sun (Vanderbilt University, USA), Shashank Shekhar (Siemens, USA), Aniruddha Gokhale, Gabor Karsai, Abhishek Dubey (Vanderbilt University, USA)
Sunstone: Navigating the Way Through the Fog
Julien Gedeon, Sebastian Zengerle, Sebastian Alles, Florian Brandherm, Max Mühlhäuser (TU Darmstadt, Germany)
Comparison of Alternative Architectures in Fog Computing
Vasileios Karagiannis, Stefan Schulte (Vienna University of Technology, Austria)
Modelling Fog Offloading Performance
Ayesha Abdul Majeed, Peter Kilpatrick, Ivor Spence, Blesson Varghese (Queen’s University Belfast, UK)
A Multi-Weight Strategy for Container Consolidation
Najet Hamdi (University of Sfax, Tunisia), Walid Chainbi (University of Sousse, Tunisia)
SessionStore: A Session-Aware Datastore for the Edge
Seyed Hossein Mortazavi, Mohammad Salehe (University of Toronto, Canada), Bharath Balasubramanian (AT&T Labs, USA), Eyal de Lara (University of Toronto, Canada), Shankaranarayanan Puzhavakath Narayanan (AT&T Labs, USA)
Priority-based Fair Scheduling in Edge Computing
Arkadiusz Madej, Nan Wang, Nikolaos Athanasopoulos (Queen’s University Belfast, UK), Rajiv Ranjan (Newcastle University, UK), Blesson Varghese (Queen’s University Belfast, UK)
Efficient Hosting of Robust IoT Applications on Edge Computing Platform
Cosmin Avasalcai (Vienna University of Technology, Austria), Bahram Zarrin, Paul Pop (Technical University of Denmark, Denmark), Schahram Dustdar (Vienna University of Technology, Austria)
Mobility-aware Computation Offloading in Edge Computing Using Prediction (Short paper)
Erfan Farhangi Maleki, Lena Mashayekhy (University of Delaware, USA)
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
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
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
Blesson Varghese - b.varghese[at]qub.ac.uk
Lena Mashayekhy - mlena[at]udel.edu