Optimising quality-of-control for data-intensive multiprocessor image-based control systems considering workload variations

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

4 Citaten (Scopus)
24 Downloads (Pure)

Samenvatting

Image-Based Control (IBC) systems have a long sample period. Sensing in these systems consists of compute-intensive image processing algorithms whose response times are dependent on image workload. IBC systems are typically designed for the worst-case workload that results in a long sample period and hence suboptimal quality-of-control (QoC). This worst-case based design is further considered for mapping of controller tasks and allocating platform resources, resulting in significant resource over-provisioning. Our design philosophy is to sample as fast as possible to optimise QoC for a given platform allocation, and for this, we present a structured design flow. Workload variations determine how fast we can sample and we model this dynamic behaviour using the concept of workload scenarios. Our choice of scenario-aware dataflow as the formal model for our application enables us to: i) model dynamic behaviour, analyse timing, and optimally map application tasks to the platform for maximising the effective utilisation of allocated resources, ii) relate throughput of the dataflow graph to the sample period, and thus combine dataflow analysis and mapping with control design parameters and QoC to identify system scenarios, and iii) to efficiently implement a run-time mechanism that manages necessary dynamic reconfiguration between system scenarios. Our results show that our design approach outperforms the worst-case based design with respect to optimising QoC and maximising effective resource utilisation.

Originele taal-2Engels
TitelProceedings - 21st Euromicro Conference on Digital System Design, DSD 2018
RedacteurenNikos Konofaos, Martin Novotny, Amund Skavhaug
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's320-327
Aantal pagina's8
ISBN van elektronische versie978-1-5386-7377-5
ISBN van geprinte versie978-1-5386-7378-2
DOI's
StatusGepubliceerd - 12 okt 2018
Evenement21st Euromicro Conference on Digital System Design, DSD 2018 - Prague, Tsjechië
Duur: 29 aug 201831 aug 2018
Congresnummer: 21
http://dsd-seaa2018.fit.cvut.cz/dsd/

Congres

Congres21st Euromicro Conference on Digital System Design, DSD 2018
Verkorte titelDSD 2018
LandTsjechië
StadPrague
Periode29/08/1831/08/18
Internet adres

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  • Citeer dit

    Mohamed, S., Zhu, D., Goswami, D., & Basten, T. (2018). Optimising quality-of-control for data-intensive multiprocessor image-based control systems considering workload variations. In N. Konofaos, M. Novotny, & A. Skavhaug (editors), Proceedings - 21st Euromicro Conference on Digital System Design, DSD 2018 (blz. 320-327). [8491834] Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/DSD.2018.00063