Online control optimization using load driven scheduling

Lui Sha; Xue Liu; Marco Caccamo; Giorgio Buttazzo

doi:10.1109/CDC.2001.914703

Online control optimization using load driven scheduling

Lui Sha
, Xue Liu
, Marco Caccamo
, Giorgio Buttazzo

Research output: Contribution to journal › Article › peer-review

30 Scopus citations

Abstract

In many real-time control applications, the task periods are typically fixed and worst-case execution times are used in schedulability analysis. With the advancement of robotics, flexible visual sensing using cameras becomes a popular alternative to the use of embedded sensors. Unfortunately, the execution time of visual tracking varies greatly. In this paper, we integrate load driven online scheduling with direct digital designs to optimize control performance as a function of varying workload.

Original language	English
Pages (from-to)	4877-4882
Number of pages	6
Journal	Proceedings of the IEEE Conference on Decision and Control
Volume	5
DOIs	https://doi.org/10.1109/CDC.2001.914703
State	Published - Dec 2000
Externally published	Yes

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10.1109/CDC.2001.914703

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title = "Online control optimization using load driven scheduling",

abstract = "In many real-time control applications, the task periods are typically fixed and worst-case execution times are used in schedulability analysis. With the advancement of robotics, flexible visual sensing using cameras becomes a popular alternative to the use of embedded sensors. Unfortunately, the execution time of visual tracking varies greatly. In this paper, we integrate load driven online scheduling with direct digital designs to optimize control performance as a function of varying workload.",

author = "Lui Sha and Xue Liu and Marco Caccamo and Giorgio Buttazzo",

year = "2000",

month = dec,

doi = "10.1109/CDC.2001.914703",

language = "English",

volume = "5",

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journal = "Proceedings of the IEEE Conference on Decision and Control",

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T1 - Online control optimization using load driven scheduling

AU - Sha, Lui

AU - Liu, Xue

AU - Caccamo, Marco

AU - Buttazzo, Giorgio

PY - 2000/12

Y1 - 2000/12

N2 - In many real-time control applications, the task periods are typically fixed and worst-case execution times are used in schedulability analysis. With the advancement of robotics, flexible visual sensing using cameras becomes a popular alternative to the use of embedded sensors. Unfortunately, the execution time of visual tracking varies greatly. In this paper, we integrate load driven online scheduling with direct digital designs to optimize control performance as a function of varying workload.

AB - In many real-time control applications, the task periods are typically fixed and worst-case execution times are used in schedulability analysis. With the advancement of robotics, flexible visual sensing using cameras becomes a popular alternative to the use of embedded sensors. Unfortunately, the execution time of visual tracking varies greatly. In this paper, we integrate load driven online scheduling with direct digital designs to optimize control performance as a function of varying workload.

UR - https://www.scopus.com/pages/publications/0034444225

U2 - 10.1109/CDC.2001.914703

DO - 10.1109/CDC.2001.914703

M3 - Article

AN - SCOPUS:0034444225

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VL - 5

SP - 4877

EP - 4882

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

ER -

Online control optimization using load driven scheduling

Abstract

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