TY - GEN
T1 - Online workload monitoring with the feedback of actual execution time for real-time systems
AU - Hu, Biao
AU - Huang, Kai
AU - Chen, Gang
AU - Cheng, Long
AU - Knoll, Alois
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/5/11
Y1 - 2017/5/11
N2 - Guaranteeing the system workload within design bounds is a basic requirement for a real-time system. Design-time bounds are usually based on worst-case activation patterns and worst-case execution time. While using the worst-case assumptions for online monitoring can guarantee the system safety, it also introduces unexplored slacks due to tasks consuming less than their worst-case execution times. In this paper, we introduce a monitoring scheme with the feedback of actual execution time for real-time systems. By using this runtime feedback instead of offline assumptions, this monitoring scheme can accept events that are considered as violations offline, and thereby improve the system utilization. In the experiments of both MATLAB simulation and MicroC/OS-II running in a softcore processor implemented on an FPGA, different probability distributions of actual execution time are used in analyzing how much the benefit can be gained from the feedback scheme.
AB - Guaranteeing the system workload within design bounds is a basic requirement for a real-time system. Design-time bounds are usually based on worst-case activation patterns and worst-case execution time. While using the worst-case assumptions for online monitoring can guarantee the system safety, it also introduces unexplored slacks due to tasks consuming less than their worst-case execution times. In this paper, we introduce a monitoring scheme with the feedback of actual execution time for real-time systems. By using this runtime feedback instead of offline assumptions, this monitoring scheme can accept events that are considered as violations offline, and thereby improve the system utilization. In the experiments of both MATLAB simulation and MicroC/OS-II running in a softcore processor implemented on an FPGA, different probability distributions of actual execution time are used in analyzing how much the benefit can be gained from the feedback scheme.
UR - https://www.scopus.com/pages/publications/85020163525
U2 - 10.23919/DATE.2017.7927092
DO - 10.23919/DATE.2017.7927092
M3 - Conference contribution
AN - SCOPUS:85020163525
T3 - Proceedings of the 2017 Design, Automation and Test in Europe, DATE 2017
SP - 764
EP - 769
BT - Proceedings of the 2017 Design, Automation and Test in Europe, DATE 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th Design, Automation and Test in Europe, DATE 2017
Y2 - 27 March 2017 through 31 March 2017
ER -