RTCSA 2020 : IEEE International Conference on Embedded and Real-Time Computing Systems and Applications

in Conferences   Posted on June 4, 2020 

Conference Information

Submission Deadline Friday 17 Apr 2020 Proceedings indexed by :
Conference Dates Aug 19, 2020 - Aug 21, 2020
Conference Address Virtual Event, Online
Conference & Submission Link https://rtcsa2020.github.io/index/
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Ranking & Metrics (This is a TOP Conference)

Impact Score 2.15
#Contributing Top Scientists 15
#Papers published by Top Scientists 20
Google Scholar H5-index 14
Number of Editions: 26 (Since 1994)
Guide2Research Overall Ranking: 426
Category Rankings
Hardware, Robotics & Electronics 76
Software Engineering & Programming 98
Proceedings https://ieeexplore.ieee.org/xpl/conhome/1000618/all-proceedings
DBLP Page https://dblp.uni-trier.de/db/conf/rtcsa

Conference Call for Papers

The 26th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications

Location: Virtual Conference
Date: August 19-21, 2020
Important Dates:

Paper Submission Deadline (extended):April 14, 2020, March 31, 2020
Paper Update Deadline: April 17, 2020
Acceptance Notification: May 20, 2020
Final Paper Submission: June 15, 2020
Conference Date: August 19-21, 2020

The RTCSA conference series (now at its 26th edition) brings together researchers and developers from academia and industry for advancing the technology and the theory to design and develop time-sensitive applications. All traditional applications in which temporal aspects need to be considered are in the scope of the conference. CPS, (Industrial) IoT, embedded systems, fog/edge/cloud computing are just notable examples. RTCSA welcomes both research and industrial papers that describe research or technical aspects in the area of embedded and real-time systems. Proceedings will be published by the IEEE Computer Society on IEEExplore and will be indexed by most search engines including Scopus, Web of Science, DBLP.

Submission of a paper should be regarded as a commitment that, should the paper be accepted, at least one of the authors will register and attend the conference to present the work. RTCSA 2020 reserves the right to exclude a paper from distribution after the conference (e.g., removal from the digital library and indexing services), if the paper is not presented at the conference.

Topic of Interest

The 26th edition of RTCSA will bring together researchers and developers from academia and industry to promote cross-fertilization and discuss advances and trends in the technology of embedded and real-time systems and their emerging applications, including the Internet of Things and Cyber-Physical Systems. RTCSA 2020 seeks papers that describe original research in the following areas, but are not limited to:

*** REAL-TIME SYSTEMS TRACK ***

Real-Time Scheduling
Workload models for real-time systems
Temperature/Energy-aware Scheduling
Scheduling over heterogeneous architectures
Scheduling over distributed architectures
Timing Analysis
Formal methods for temporal guarantees
Programming Languages and Run-Time Systems
Middleware Systems
Communication Networks and Protocols of Real-Time Systems
Time-Sensitive Media Processing and Transmissions
Latency and throughput in Real-Time Databases

*** IoT, CPS, AND EMERGING APPLICATIONS TRACK ***

Systems, Technology and Foundations of IoT and CPS
Applications and Case Studies of IoT and CPS
Smart and Connected Health
Industrial Internet and Industry 4.0
Smart City Technology and Applications
Smart Transportation and Infrastructure
Cyber-Physical Co-Design
Medical CPS
Cloud, Middleware and Networks for IoT and CPS
Wireless Sensor-Actuator Networks for IoT and CPS

*** EMBEDDED SYSTEMS TRACK ***

Multi-Core Embedded Systems
Operating Systems
Non-Volatile Memory and Storage
Power/Thermal Aware Design
Fault Tolerance and Security
Sensor-based Systems and Applications
Reconfigurable Computing Architectures and Software Support
Ubiquitous and Distributed Embedded Systems and Networks
Embedded Systems for Machine-Learning

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