Discrete Dynamics in Nature and Society

Performance Analysis and Synthetisation of Complex Systems with Event-triggered Communication Scheduling


Publishing date
01 May 2021
Status
Published
Submission deadline
25 Dec 2020

Lead Editor
Guest Editors

1University of Shanghai for Science and Technology, Shanghai, China

2University of New South Wales, Sydney, Australia


Performance Analysis and Synthetisation of Complex Systems with Event-triggered Communication Scheduling

Description

Recent years have witnessed a growing number of publications reporting on complex systems, owing to their extensive applications in the natural sciences and in industry fields. Due to the utilisation of shared networks, data exchange could be governed by event-based scheduling protocols to cater for the requirements of efficient communication bandwidth usages, reduced computational cost, as well as lower sensing/actuation frequencies. Furthermore, the distributed characteristics of complex systems lead to the urgent requirements of distributed sensing and computation. There is no doubt that the system dynamics and performance analysis become much more complex than those already studied in non-networked scenarios. Thereby, it raises an ever-increasing need for research in developing novel methodologies to deal with the corresponding performance analysis and synthesis.

Complex systems with event-triggered communication scheduling focus on the resource-limited execution of sensing, actuation, and decision-making in the field of cybernetics, especially in signal processing and networked control across the natural sciences and across industry fields.

This Special Issue aims to provide a research venue for exchanging and discussing the technical trends and challenges of complex systems with event-triggered communication scheduling. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

  • Event-based synchronisation analysis of complex networks
  • Performance analysis of complex networked systems
  • Event-based state estimation of neural networks
  • Event-based state estimation of sensor networks
  • Event-based control of multi-agent systems
  • Control and filtering of complex networked systems with other communication scheduling
  • Security control and filtering of complex networked systems
  • Event-based control and signal processing
  • Event-driven sampling techniques for networked systems
Discrete Dynamics in Nature and Society
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Acceptance rate13%
Submission to final decision127 days
Acceptance to publication23 days
CiteScore2.000
Journal Citation Indicator0.410
Impact Factor1.4
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