[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
xkzhou2010 at gmail.com
Thu Feb 23 07:21:24 CET 2023
[Apologies for multiple postings]
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.
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.
Xiaokang Zhou, on behalf of guest editors
[JSA Call for Papers]
Journal of Systems Architecture
Special Issue on
Distributed Learning and Blockchain Enabled
for Next Generation of Big Data Driven Cyber-Physical
Aims and Scope
Modern Cyber-Physical System (CPS) is composed by integrating and
networking the physical world, computational components, and
devices such as sensors, actuators, etc. Typical CPS applications include
autonomous driving systems, smart home, robotics systems, smart healthcare
etc. With the prevalence of CPSs, the huge volume of ever-increasing data
produced by heterogeneous IoT devices raise crucial challenges in both
architectures and data management. First, traditional centralized CPSs have
the shortcomings of destitute transparency and scalability, making it
to scale with the ever-increasing volume of data generated across CPSs.
Moreover, CPSs are often associated with sensitive data, while their
infrastructures expose them to vulnerability, data breaches, and denial of
Therefore, the decentralized CPS infrastructure becomes a potential
solution, in particular, it is essential to explore new big data processing
with decentralized CPS infrastructures.
Distributed learning and blockchain techniques, envisioned as the bedrock
of future intelligent networks and IoT technologies, have attracted
attentions from both academy and industry due to the nature of
decentralization, data security, and privacy benefits. The decentralized
together with the ability to enable secured, trusted and decentralized
autonomous ecosystems, revolutionize increasingly centralized CPSs for
and applications, as well as reshaping of traditional data mining and
knowledge discovery patterns. However, adopting distributed learning and
technologies in big data driven CPS applications requires essential
insights with respect to concrete application domains, scalability, privacy
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
⠂ Distributed learning and blockchain in cloud/edge/fog computing for CPSs
⠂ Distributed learning and blockchain based lightweight data structure for
⠂ 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
Submissions should be made online at https://www.editorialmanager.com/jsa/.
Please select the “VSI:DL&BCforBDdrivenCPS” option as type of the paper.
• Open for submissions: 31st March 2023
• Acceptance deadline: 30th September 2023
• 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
Corresponding Guest Editor, Dr. Zhou (zhou at biwako.shiga-u.ac.jp)
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