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Feedback-based resource management for multi-threaded applications

Fulltext:


Authors:

Alessandro Papadopoulos, Kunal Agrawal , Enrico Bini , Sanjoy Baruah

Publication Type:

Journal article

Venue:

Real-Time Systems

Publisher:

Springer Nature

DOI:

10.1007/s11241-022-09386-7


Abstract

Reconciling the constraint of guaranteeing to always meet deadlines with the optimization objective of reducing waste of computing capacity lies at the heart of a large body of research on real-time systems. Most approaches to doing so require the application designer to specify a deeper characterization of the workload (and perhaps extensive profiling of its run-time behavior), which then enables shaping the resource assignment to the application. In practice, such approaches are weak as they load the designer with the heavy duty of a detailed workload characterization. We seek approaches for reducing the waste of computing resources for recurrent real-time workloads in the absence of such additional characterization, by monitoring the minimal information that needs to be observable about the run-time behavior of a real-time system: its response time. We propose two resource control strategies to assign resources: one based on binary-exponential search and the other, on principles of control. Both approaches are compared against the clairvoyant scenario in which the average/typical behavior is known. Via an extensive simulation, we show that both techniques are useful approaches to reducing resource computation while meeting hard deadlines.

Bibtex

@article{Papadopoulos6489,
author = {Alessandro Papadopoulos and Kunal Agrawal and Enrico Bini and Sanjoy Baruah},
title = {Feedback-based resource management for multi-threaded applications},
pages = {1--34},
month = {July},
year = {2022},
journal = {Real-Time Systems},
publisher = {Springer Nature},
url = {http://www.es.mdh.se/publications/6489-}
}