Call-for-Papers
Emerging Information Processing and Management Paradigms: Edge Intelligence, Federated Learning, and Blockchain (VSI: IPMC2022 EMERGING)

A Special Issue for Information Processing & Management (IP&M), Elsevier

Note: This special issue is a Thematic Track at IP&MC2022. For more information about IP&MC2022, please visit https://www.elsevier.com/events/conferences/information-processing-and-management-conference.

Title of the Special Issue

Emerging Information Processing and Management Paradigms: Edge Intelligence, Federated Learning, and Blockchain(VSI: IPMC2022 EMERGING)

Track Editors:

Yaser Jararweh, Duquesne University, USA (yaser.amd@gmail.com) (Managing Editor)
Feras Awaysheh, University of Tartu, Estonia (feras.awaysheh@ut.ee)
Moayad Aloqaily, MBZUAI, UAE(maloqaily@ieee.org)
Nadra Guizani, University of Texas Arlington, USA (nadra.guizani@uta.edu)
Yuli Yang, University of Lincoln, United Kingdom (yyang@lincoln.ac.uk)

Aims and Scope:

Our ever-increasing ability to allocate, process, and extract valuable information at the network's edge triggered many modern applications like autonomous vehicles, network softwarization, smart cities applications, connected health systems, and industrial IoT, etc. However, such applications require high communication latency with real-time response and trustworthy models. Decentralizing the data analytics beyond the traditional cloud silos is critical, with several requirements to be accommodated. The recent emerging edge/fog capacities as a supporting and complementary infrastructure for the centralized cloud systems provide a golden opportunity by harnessing decentralized machine intelligence abilities to make decisions in the right place and time. Moreover, the emergence of distributed machine learning techniques with specific applications of Federated Learning improves user data privacy and trust throughout the complete system being applied.

A futuristic paradigm spear-headed known as Edge Intelligence (EI) is taking shape so that AI/ML services occur close to where data is captured. EI is expected to improve the agility of big data services and leverage resources located at the edge of the network and along the continuum between the cloud and the IoT. Nevertheless, addressing the deployment complexity, security, privacy, and trust of the edge resources is of paramount importance. Also, achieving this vision required synergizing the border communication system advances, including big data, distributed machine learning, Blockchain technology, and privacy-preserving federated learning.

The main objective of this track is to solicit papers at the intersection of these technologies. This track will provide a venue for researchers, scientists, industry experts, and practitioners to share their novel research results on recent advances in Edge Intelligence, Federated Learning, and Blockchain architectures and applications. High-quality research contributions describing original and unpublished constructive, empirical, experimental, and theoretical work in EI are invited to submit their timely findings.
Recommended Topics:

Topics to be discussed in this track include (but are not limited to) Architectures and Applications in the following:

Distributed and federated machine learning in edge computing
Theory and Applications of EI
Middleware and runtime systems for EI
Programming models compliant with EI
Scheduling and resource management for EI
Data allocation and application placement strategies for EI
Osmotic computing with edge continuum, Microservices and MicroData architectures
ML/AI models and algorithms for load balancing
Theory and Applications of federated learning
Federated learning and privacy-preserving large-scale data analytics
MLOps and ML pipelines at edge computing
Transfer learning, interactive learning, and Reinforcement Learning for edge computing
Modelling and simulation of EI and edge-to-cloud environments
Security, privacy, trust, and provenance issues in edge computing
Distributed consensus and blockchains at edge architecture
Blockchain networking for Edge Computing Architecture
Blockchain technology for Edge Computing Security
Blockchain-based access controls for Edge-to-cloud continuum
Blockchain-enabled solutions for Cloud and Edge/Fog IoT systems
Forensic Data Analytics compliant with EI

Important Dates
Online submission system is open January 5, 2022
Thematic track manuscript submission due date; authors are welcome to submit early as reviews will be rolling June 15, 2022
Author notification July 31, 2022
IP&MC conference presentation and feedback October 20-23, 2022
Post conference revision due date, but authors welcome to submit earlier January 1, 2023


Submission Guidelines

Submit your manuscript to the Special Issue category (VSI: IPMC2022 EMERGING) through the online submission system of Information Processing & Management:

https://www.editorialmanager.com/ipm/

Authors will prepare the submission following the Guide for Authors on IP&M journal at (https://www.elsevier.com/journals/information-processing-and-management/0306-4573/guide-for-authors). All papers will be peer-reviewed following the IP&MC2022 reviewing procedures.

The authors of accepted papers will be obligated to participate in IP&MC 2022 and present the paper to the community to receive feedback. The accepted papers will be invited for revision after receiving feedback on the IP&MC 2022 conference. The submissions will be given premium handling at IP&M following its peer-review procedure and, (if accepted), published in IP&M as full journal articles, with also an option for a short conference version at IP&MC2022.

Please see this infographic for the manuscript flow:
https://www.elsevier.com/__data/assets/pdf_file/0003/1211934/IPMC2022Timeline10Oct2022.pdf

For more information about IP&MC2022, please visit:https://www.elsevier.com/events/conferences/information-processing-and-management-conference