Call for Papers |
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2nd International Workshop on Distributed Machine Learning for the Intelligent Computing Continuum (DML-ICC) In conjunction with the 15th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2022) December 6-9, 2022 Portland, Oregon, USA http://www.lrc.ic.unicamp.br/dml-icc/ ### Background ### As the cloud extends to the fog and to the edge, computing services can be scattered over a set of computing resources that encompass users’ devices, the cloud, and intermediate computing infrastructure deployed in between. Moreover, increasing networking capacity promises lower delays in data transfers, enabling a continuum of computing capacity that can be used to process large amounts of data with reduced response times. Such large amounts of data are frequently processed through machine learning approaches, seeking to extract knowledge from raw data generated and consumed by a widely heterogeneous set of applications. Distributed machine learning has been evolving as a tool to run learning tasks also at the edge, often immediately after the data is produced, instead of transferring data to the centralized cloud for later aggregation and processing. Following the successful DML-ICC 2021, this second edition of DML-ICC keeps the aim to be a forum for discussion among researchers with a distributed machine learning background and researchers from parallel/distributed systems and computer networks. By bringing together these research topics, we look forward in building an Intelligent Computing Continuum, where distributed machine learning models can seamlessly run on any device from the edge to the cloud, creating a distributed computing system that is able to fulfill highly heterogeneous applications requirements and build knowledge from data generated by these applications. ### Topics ### DML-ICC 2022 workshop aims to attract researchers from the machine learning community, especially the ones involved with distributed machine learning techniques, and researchers from the parallel/distributed computing communities. Together, these researchers will be able to build resource management mechanisms that are able to fulfill machine learning jobs requirements, but also use machine learning techniques to improve resource management in large distributed systems. Topics of interest include but are not limited to: - Autonomic Computing in the Continuum - Business and Cost Models for the Computing Continuum - Complex Event Processing and Stream Processing - Computing and Networking Slicing for the Continuum - Distributed Machine Learning for Resource Management and Scheduling - Distributed Machine Learning in the Computing Continuum - Distributed Machine Learning applications - Distribute Machine Learning performance evaluation - Federated Learning - Intelligent Computing Continuum architectures and models - Management of Distributed Learning Tasks - Mobility support in the Computing Continuum - Network management in the Computing Continuum - Privacy using Distributed Learning - Programming models for the Computing Continuum - Resource management and Scheduling in the computing continuum - Smart Environments (Smart Cities, Smart Buildings, Smart Industry, etc.) - Theoretical Modeling for the Computing Continuum ### Submissions ### Paper submission is through Easychair:https://easychair.org/conferences/?conf=dmlicc2022 The DML-ICC workshop invites authors to submit original and unpublished work. Papers should not exceed 6 pages in IEEE format. Up to two additional pages might be purchased upon the approval of the proceedings chair. All selected papers for this workshop are peer-reviewed and will be published in IEEE Xplore and ACM Digital Library. Submission requires the willingness of at least one of the authors to register and present the paper. Please check the DML-ICC webpage for more details on paper format: http://www.lrc.ic.unicamp.br/dml-icc/ ### Important Dates ### Paper submission: 15 September, 2022 (extended, hard deadline) Notification of Authors: 05 October , 2022 Camera ready submission: 15 October, 2022 Workshop date: Exact date to be defined (6-9 December 2022) ### Workshop Chairs ### - Ian Foster, University of Chicago and Argonne National Laboratory, USA - Filip De Turck (Ghent University, Belgium) - Luiz Bittencourt, University of Campinas, Brazil ### Program Committee (preliminary - to be updated) ### - Gabriel Antoniu, Inria, France - Rodrigo Calheiros, Western Sydney University, Australia - Roch Glitho, Concordia University, Canada - Carlos Kamienski, Federal University of ABC, Brazil - Wei Li, University of Sydney, Australia - Zoltán Mann, University of Duisburg-Essen, Germany - Radu Prodan, University of Klagenfurt, Austria - Omer Rana, Cardiff University, United Kingdom - Christian Esteve Rothenberg, University of Campinas, Brazil - Rizos Sakellariou, University of Manchester, United Kingdom - Josef Spillner, Zurich University of Applied Sciences, Switzerland - Javid Taheri, Karlstad University, Sweden - Massimo Villari, University of Messina, Italy |
Summary |
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DML-ICC 2022 : 2nd Workshop on Distributed Machine Learning for the Intelligent Computing Continuum will take place in Portland, Oregon, USA. It’s a 4 days event starting on Dec 6, 2022 (Tuesday) and will be winded up on Dec 9, 2022 (Friday). DML-ICC 2022 falls under the following areas: DISTRIBUTED MACHINE LEARNING, COMPUTING CONTINUUM, CLOUD COMPUTING, EDGE COMPUTING, etc. Submissions for this Workshop can be made by Sep 15, 2022. Authors can expect the result of submission by Oct 5, 2022. Upon acceptance, authors should submit the final version of the manuscript on or before Oct 15, 2022 to the official website of the Workshop. Please check the official event website for possible changes before you make any travelling arrangements. Generally, events are strict with their deadlines. It is advisable to check the official website for all the deadlines. Other Details of the DML-ICC 2022
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Credits and Sources |
| [1] DML-ICC 2022 : 2nd Workshop on Distributed Machine Learning for the Intelligent Computing Continuum |
