TY - GEN
T1 - Improving performance by monitoring while maintaining worst-case guarantees
AU - Abdullah, Syed Md Jakaria
AU - Lampka, Kai
AU - Yi, Wang
N1 - Publisher Copyright:
© 2016 EDAA.
PY - 2016/4/25
Y1 - 2016/4/25
N2 - With real-time systems, feasibility analysis is based on worst-case scenarios. At run-time, worst-case situations are often very unlikely to occur. With the system being dimensioned for the worst-case, one faces low resource utilization and implicit loss in performance at run-time. We propose to use run-time monitoring for evaluating the deviation of job releases from their worst-case release bound. This allows us to compute a conservative bound on the future workload. Based on this, we design a scheme for reclaiming computation time, which has been originally allocated for jobs which are now known to be absent. By organizing the consumption of extra computing time in a dynamic and time-safe manner, we improve the run-time performance of applications and provably maintain the worst-case guarantees for their response times. We evaluate the usefulness of the presented approach by using randomly generated traces of job releases.
AB - With real-time systems, feasibility analysis is based on worst-case scenarios. At run-time, worst-case situations are often very unlikely to occur. With the system being dimensioned for the worst-case, one faces low resource utilization and implicit loss in performance at run-time. We propose to use run-time monitoring for evaluating the deviation of job releases from their worst-case release bound. This allows us to compute a conservative bound on the future workload. Based on this, we design a scheme for reclaiming computation time, which has been originally allocated for jobs which are now known to be absent. By organizing the consumption of extra computing time in a dynamic and time-safe manner, we improve the run-time performance of applications and provably maintain the worst-case guarantees for their response times. We evaluate the usefulness of the presented approach by using randomly generated traces of job releases.
UR - https://www.scopus.com/pages/publications/84973623279
M3 - 会议稿件
AN - SCOPUS:84973623279
T3 - Proceedings of the 2016 Design, Automation and Test in Europe Conference and Exhibition, DATE 2016
SP - 257
EP - 260
BT - Proceedings of the 2016 Design, Automation and Test in Europe Conference and Exhibition, DATE 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 19th Design, Automation and Test in Europe Conference and Exhibition, DATE 2016
Y2 - 14 March 2016 through 18 March 2016
ER -