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*Special Issue on Emerging Information Processing and Management Paradigms:
Edge Intelligence, Federated Learning, and Blockchain *

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

*Note*: This special issue is a Thematic Track at IP&MC2022 conference, The
authors of accepted papers will be obligated to participate in IP&MC 2022
and present the paper

to the community to receive feedback.

*For more information about IP&MC2022, please visit*
< >

*IP&MC2022 will take during 20-23 October 2022 | Xiamen, China *


*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

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
   - 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
   - Modeling 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*

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

*Track Editors:*

   - Yaser Jararweh, Duquesne University, USA ([log in to unmask])
   (Managing Editor)
   - Feras Awaysheh, University of Tartu, Estonia ([log in to unmask])
   - Moayad Aloqaily, MBZUAI, UAE([log in to unmask] <[log in to unmask]>)
   - Nadra Guizani, University of Texas Arlington, USA (
   [log in to unmask])
   - Yuli Yang, University of Lincoln, United Kingdom ([log in to unmask])

* Submission Guidelines*

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

Authors will prepare the submission following the Guide for Authors on IP&M
journal at ( ).
All papers will be peer-reviewed following the IP&MC2022 reviewing

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: 

For more information about IP&MC2022, please visit: 

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