[Om-announce] CFP to Special Issue in Journal of Systems Architecture on Distributed Learning and Blockchain Enabled Infrastructures for Next Generation of Big Data Driven Cyber-Physical Systems - Deadline Mar. 31, 2023

[Xiaokang Zhou]

[Apologies for multiple postings]

Dear Professor(Dr.),

It is my pleasure and honor to share you this information of CFP in the
Journal of Systems Architecture.

Please consider submitting a paper to a Special Issue on "Distributed
Learning and Blockchain Enabled Infrastructures for Next Generation of Big
Data Driven Cyber-Physical Systems" for Journal of Systems Architecture.
The deadline is extended to Mar. 31, 2023.
https://www.sciencedirect.com/journal/journal-of-systems-architecture/about/call-for-papers#distributed-learning-and-blockchain-enabled-infrastructures-for-next-generation-of-big-data-driven-cyber-physical-systems

Also, please kindly help distribute the CFP (see following) and encourage
your colleagues, friends, and students to make submissions. Your strong
supports are highly appreciated.


Best regards,
Xiaokang Zhou, on behalf of guest editors


[JSA Call for Papers]
===========================================================================================
                                 Journal of Systems Architecture

                                         Special Issue on

                   Distributed Learning and Blockchain Enabled
Infrastructures
                  for Next Generation of Big Data Driven Cyber-Physical
Systems

-----------------------------------------------------------------------------------------------------------------------

Aims and Scope
Modern Cyber-Physical System (CPS) is composed by integrating and
networking the physical world, computational components, and
Internet-of-Things(IoT)
devices such as sensors, actuators, etc. Typical CPS applications include
autonomous driving systems, smart home, robotics systems, smart healthcare
systems,
etc. With the prevalence of CPSs, the huge volume of ever-increasing data
produced by heterogeneous IoT devices raise crucial challenges in both
system
architectures and data management. First, traditional centralized CPSs have
the shortcomings of destitute transparency and scalability, making it
difficult
to scale with the ever-increasing volume of data generated across CPSs.
Moreover, CPSs are often associated with sensitive data, while their
centralized
infrastructures expose them to vulnerability, data breaches, and denial of
services.

Therefore, the decentralized CPS infrastructure becomes a potential
solution, in particular, it is essential to explore new big data processing
techniques
with decentralized CPS infrastructures.

Distributed learning and blockchain techniques, envisioned as the bedrock
of future intelligent networks and IoT technologies, have attracted
tremendous
attentions from both academy and industry due to the nature of
decentralization, data security, and privacy benefits. The decentralized
architectures,
together with the ability to enable secured, trusted and decentralized
autonomous ecosystems, revolutionize increasingly centralized CPSs for
infrastructures
and applications, as well as reshaping of traditional data mining and
knowledge discovery patterns. However, adopting distributed learning and
blockchain
technologies in big data driven CPS applications requires essential
insights with respect to concrete application domains, scalability, privacy
issues,
performance, and financial benefits as well.

Topics may include (but are not limited to):

⠂ Data and transaction management on blockchain in CPSs
⠂ Distributed data analytics in blockchain enabled CPSs
⠂ Data mining and knowledge discovery over distributed learning in CPSs
⠂ Novel distributed learning models with strict resource constraints in CPSs
⠂ Distributed learning for emerging applications in CPSs
⠂ Data security, privacy and trust on distributed learning and blockchain
in CPSs
⠂ Distributed learning and blockchain in cloud/edge/fog computing for CPSs
⠂ Distributed learning and blockchain based lightweight data structure for
CPS data
⠂ Big data algorithms, tools and services using distributed learning and
blockchain technologies in CPSs
⠂ Performance optimization and energy efficiency for distributed learning
and blockchain enabled big data applications in CPSs

Manuscript submission information
General information for submitting papers to JSA can be found at
https://www.journals.elsevier.com/journal-of-systems-architecture.
Submissions should be made online at https://www.editorialmanager.com/jsa/.
Please select the “VSI:DL&BCforBDdrivenCPS” option as type of the paper.

Important Dates
• Open for submissions:                31st March 2023
• Acceptance deadline:                 30th September 2023

Guest editors:
• Dr. Xiaokang Zhou, Shiga University, Japan
• Dr. Giancarlo Fortino, University of Calabria, Italy
• Dr. Carson Leung, University of Manitoba, Canada
• Dr. Mohammad Hammoudeh, King Fahd University of Petroleum & Mineral

Contact Information
Corresponding Guest Editor, Dr. Zhou (zhou at biwako.shiga-u.ac.jp)
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