***** To join INSNA, visit http://www.insna.org *****

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 https://www.elsevier.com/events/conferences/information-processing-and-management-conference.

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

 

Call-for-Papers

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
  • 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:


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

 


_____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.