Dynamic distribution of robot control components under hard realtime constraints – Modeling, experimental results and practical considerations
It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Dietrich, Franz [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013transfer abstract |
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| Schlagwörter: |
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| Umfang: |
20 |
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| Übergeordnetes Werk: |
Enthalten in: Discovery of a second generation agonist of the orphan G-protein coupled receptor GPR119 with an improved profile - 2012, JSA : the EUROMICRO journal, Amsterdam |
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| Übergeordnetes Werk: |
volume:59 ; year:2013 ; number:10 ; pages:1047-1066 ; extent:20 |
| Links: |
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| DOI / URN: |
10.1016/j.sysarc.2012.12.001 |
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ELV021635420 |
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| 245 | 1 | 0 | |a Dynamic distribution of robot control components under hard realtime constraints – Modeling, experimental results and practical considerations |
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| 520 | |a It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across multiple hosts, this article proposes to introduce aspects of self-management into robot control architectures. It is proposed to use graph partitioning algorithms to determine the distribution pattern (mapping of control tasks to CPU resources while minimizing bus communication load). The underlying model and the respective analysis guarantee that, after adaption of the distribution pattern, real-time properties are preserved and load is balanced. In this way, poor a priori assumptions about worst-case execution times are detected and corrected continuously during runtime. This is a considerable improvement in comparison to using only offline analysis of worst-case execution times. | ||
| 520 | |a It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across multiple hosts, this article proposes to introduce aspects of self-management into robot control architectures. It is proposed to use graph partitioning algorithms to determine the distribution pattern (mapping of control tasks to CPU resources while minimizing bus communication load). The underlying model and the respective analysis guarantee that, after adaption of the distribution pattern, real-time properties are preserved and load is balanced. In this way, poor a priori assumptions about worst-case execution times are detected and corrected continuously during runtime. This is a considerable improvement in comparison to using only offline analysis of worst-case execution times. | ||
| 650 | 7 | |a Self-management |2 Elsevier | |
| 650 | 7 | |a Worst case execution time analysis |2 Elsevier | |
| 650 | 7 | |a Distributed computing |2 Elsevier | |
| 650 | 7 | |a Robot control architecture |2 Elsevier | |
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| 700 | 1 | |a Hagner, Matthias |4 oth | |
| 700 | 1 | |a Steiner, Jens |4 oth | |
| 700 | 1 | |a Goltz, Ursula |4 oth | |
| 700 | 1 | |a Raatz, Annika |4 oth | |
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10.1016/j.sysarc.2012.12.001 doi GBVA2013002000014.pica (DE-627)ELV021635420 (ELSEVIER)S1383-7621(13)00002-7 DE-627 ger DE-627 rakwb eng 004 004 DE-600 540 VZ 610 VZ 630 VZ 22 ssgn 46.00 bkl Dietrich, Franz verfasserin aut Dynamic distribution of robot control components under hard realtime constraints – Modeling, experimental results and practical considerations 2013transfer abstract 20 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across multiple hosts, this article proposes to introduce aspects of self-management into robot control architectures. It is proposed to use graph partitioning algorithms to determine the distribution pattern (mapping of control tasks to CPU resources while minimizing bus communication load). The underlying model and the respective analysis guarantee that, after adaption of the distribution pattern, real-time properties are preserved and load is balanced. In this way, poor a priori assumptions about worst-case execution times are detected and corrected continuously during runtime. This is a considerable improvement in comparison to using only offline analysis of worst-case execution times. It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across multiple hosts, this article proposes to introduce aspects of self-management into robot control architectures. It is proposed to use graph partitioning algorithms to determine the distribution pattern (mapping of control tasks to CPU resources while minimizing bus communication load). The underlying model and the respective analysis guarantee that, after adaption of the distribution pattern, real-time properties are preserved and load is balanced. In this way, poor a priori assumptions about worst-case execution times are detected and corrected continuously during runtime. This is a considerable improvement in comparison to using only offline analysis of worst-case execution times. Self-management Elsevier Worst case execution time analysis Elsevier Distributed computing Elsevier Robot control architecture Elsevier Maaß, Jochen oth Hagner, Matthias oth Steiner, Jens oth Goltz, Ursula oth Raatz, Annika oth Enthalten in Elsevier Discovery of a second generation agonist of the orphan G-protein coupled receptor GPR119 with an improved profile 2012 JSA : the EUROMICRO journal Amsterdam (DE-627)ELV011208724 volume:59 year:2013 number:10 pages:1047-1066 extent:20 https://doi.org/10.1016/j.sysarc.2012.12.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_21 GBV_ILN_22 GBV_ILN_26 GBV_ILN_40 GBV_ILN_70 GBV_ILN_72 GBV_ILN_640 GBV_ILN_2001 GBV_ILN_2002 GBV_ILN_2003 GBV_ILN_2007 46.00 Tiermedizin: Allgemeines VZ AR 59 2013 10 1047-1066 20 045F 004 |
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10.1016/j.sysarc.2012.12.001 doi GBVA2013002000014.pica (DE-627)ELV021635420 (ELSEVIER)S1383-7621(13)00002-7 DE-627 ger DE-627 rakwb eng 004 004 DE-600 540 VZ 610 VZ 630 VZ 22 ssgn 46.00 bkl Dietrich, Franz verfasserin aut Dynamic distribution of robot control components under hard realtime constraints – Modeling, experimental results and practical considerations 2013transfer abstract 20 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across multiple hosts, this article proposes to introduce aspects of self-management into robot control architectures. It is proposed to use graph partitioning algorithms to determine the distribution pattern (mapping of control tasks to CPU resources while minimizing bus communication load). The underlying model and the respective analysis guarantee that, after adaption of the distribution pattern, real-time properties are preserved and load is balanced. In this way, poor a priori assumptions about worst-case execution times are detected and corrected continuously during runtime. This is a considerable improvement in comparison to using only offline analysis of worst-case execution times. It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across multiple hosts, this article proposes to introduce aspects of self-management into robot control architectures. It is proposed to use graph partitioning algorithms to determine the distribution pattern (mapping of control tasks to CPU resources while minimizing bus communication load). The underlying model and the respective analysis guarantee that, after adaption of the distribution pattern, real-time properties are preserved and load is balanced. In this way, poor a priori assumptions about worst-case execution times are detected and corrected continuously during runtime. This is a considerable improvement in comparison to using only offline analysis of worst-case execution times. Self-management Elsevier Worst case execution time analysis Elsevier Distributed computing Elsevier Robot control architecture Elsevier Maaß, Jochen oth Hagner, Matthias oth Steiner, Jens oth Goltz, Ursula oth Raatz, Annika oth Enthalten in Elsevier Discovery of a second generation agonist of the orphan G-protein coupled receptor GPR119 with an improved profile 2012 JSA : the EUROMICRO journal Amsterdam (DE-627)ELV011208724 volume:59 year:2013 number:10 pages:1047-1066 extent:20 https://doi.org/10.1016/j.sysarc.2012.12.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_21 GBV_ILN_22 GBV_ILN_26 GBV_ILN_40 GBV_ILN_70 GBV_ILN_72 GBV_ILN_640 GBV_ILN_2001 GBV_ILN_2002 GBV_ILN_2003 GBV_ILN_2007 46.00 Tiermedizin: Allgemeines VZ AR 59 2013 10 1047-1066 20 045F 004 |
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10.1016/j.sysarc.2012.12.001 doi GBVA2013002000014.pica (DE-627)ELV021635420 (ELSEVIER)S1383-7621(13)00002-7 DE-627 ger DE-627 rakwb eng 004 004 DE-600 540 VZ 610 VZ 630 VZ 22 ssgn 46.00 bkl Dietrich, Franz verfasserin aut Dynamic distribution of robot control components under hard realtime constraints – Modeling, experimental results and practical considerations 2013transfer abstract 20 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across multiple hosts, this article proposes to introduce aspects of self-management into robot control architectures. It is proposed to use graph partitioning algorithms to determine the distribution pattern (mapping of control tasks to CPU resources while minimizing bus communication load). The underlying model and the respective analysis guarantee that, after adaption of the distribution pattern, real-time properties are preserved and load is balanced. In this way, poor a priori assumptions about worst-case execution times are detected and corrected continuously during runtime. This is a considerable improvement in comparison to using only offline analysis of worst-case execution times. It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across multiple hosts, this article proposes to introduce aspects of self-management into robot control architectures. It is proposed to use graph partitioning algorithms to determine the distribution pattern (mapping of control tasks to CPU resources while minimizing bus communication load). The underlying model and the respective analysis guarantee that, after adaption of the distribution pattern, real-time properties are preserved and load is balanced. In this way, poor a priori assumptions about worst-case execution times are detected and corrected continuously during runtime. This is a considerable improvement in comparison to using only offline analysis of worst-case execution times. Self-management Elsevier Worst case execution time analysis Elsevier Distributed computing Elsevier Robot control architecture Elsevier Maaß, Jochen oth Hagner, Matthias oth Steiner, Jens oth Goltz, Ursula oth Raatz, Annika oth Enthalten in Elsevier Discovery of a second generation agonist of the orphan G-protein coupled receptor GPR119 with an improved profile 2012 JSA : the EUROMICRO journal Amsterdam (DE-627)ELV011208724 volume:59 year:2013 number:10 pages:1047-1066 extent:20 https://doi.org/10.1016/j.sysarc.2012.12.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_21 GBV_ILN_22 GBV_ILN_26 GBV_ILN_40 GBV_ILN_70 GBV_ILN_72 GBV_ILN_640 GBV_ILN_2001 GBV_ILN_2002 GBV_ILN_2003 GBV_ILN_2007 46.00 Tiermedizin: Allgemeines VZ AR 59 2013 10 1047-1066 20 045F 004 |
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10.1016/j.sysarc.2012.12.001 doi GBVA2013002000014.pica (DE-627)ELV021635420 (ELSEVIER)S1383-7621(13)00002-7 DE-627 ger DE-627 rakwb eng 004 004 DE-600 540 VZ 610 VZ 630 VZ 22 ssgn 46.00 bkl Dietrich, Franz verfasserin aut Dynamic distribution of robot control components under hard realtime constraints – Modeling, experimental results and practical considerations 2013transfer abstract 20 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across multiple hosts, this article proposes to introduce aspects of self-management into robot control architectures. It is proposed to use graph partitioning algorithms to determine the distribution pattern (mapping of control tasks to CPU resources while minimizing bus communication load). The underlying model and the respective analysis guarantee that, after adaption of the distribution pattern, real-time properties are preserved and load is balanced. In this way, poor a priori assumptions about worst-case execution times are detected and corrected continuously during runtime. This is a considerable improvement in comparison to using only offline analysis of worst-case execution times. It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across multiple hosts, this article proposes to introduce aspects of self-management into robot control architectures. It is proposed to use graph partitioning algorithms to determine the distribution pattern (mapping of control tasks to CPU resources while minimizing bus communication load). The underlying model and the respective analysis guarantee that, after adaption of the distribution pattern, real-time properties are preserved and load is balanced. In this way, poor a priori assumptions about worst-case execution times are detected and corrected continuously during runtime. This is a considerable improvement in comparison to using only offline analysis of worst-case execution times. Self-management Elsevier Worst case execution time analysis Elsevier Distributed computing Elsevier Robot control architecture Elsevier Maaß, Jochen oth Hagner, Matthias oth Steiner, Jens oth Goltz, Ursula oth Raatz, Annika oth Enthalten in Elsevier Discovery of a second generation agonist of the orphan G-protein coupled receptor GPR119 with an improved profile 2012 JSA : the EUROMICRO journal Amsterdam (DE-627)ELV011208724 volume:59 year:2013 number:10 pages:1047-1066 extent:20 https://doi.org/10.1016/j.sysarc.2012.12.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_21 GBV_ILN_22 GBV_ILN_26 GBV_ILN_40 GBV_ILN_70 GBV_ILN_72 GBV_ILN_640 GBV_ILN_2001 GBV_ILN_2002 GBV_ILN_2003 GBV_ILN_2007 46.00 Tiermedizin: Allgemeines VZ AR 59 2013 10 1047-1066 20 045F 004 |
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10.1016/j.sysarc.2012.12.001 doi GBVA2013002000014.pica (DE-627)ELV021635420 (ELSEVIER)S1383-7621(13)00002-7 DE-627 ger DE-627 rakwb eng 004 004 DE-600 540 VZ 610 VZ 630 VZ 22 ssgn 46.00 bkl Dietrich, Franz verfasserin aut Dynamic distribution of robot control components under hard realtime constraints – Modeling, experimental results and practical considerations 2013transfer abstract 20 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across multiple hosts, this article proposes to introduce aspects of self-management into robot control architectures. It is proposed to use graph partitioning algorithms to determine the distribution pattern (mapping of control tasks to CPU resources while minimizing bus communication load). The underlying model and the respective analysis guarantee that, after adaption of the distribution pattern, real-time properties are preserved and load is balanced. In this way, poor a priori assumptions about worst-case execution times are detected and corrected continuously during runtime. This is a considerable improvement in comparison to using only offline analysis of worst-case execution times. It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across multiple hosts, this article proposes to introduce aspects of self-management into robot control architectures. It is proposed to use graph partitioning algorithms to determine the distribution pattern (mapping of control tasks to CPU resources while minimizing bus communication load). The underlying model and the respective analysis guarantee that, after adaption of the distribution pattern, real-time properties are preserved and load is balanced. In this way, poor a priori assumptions about worst-case execution times are detected and corrected continuously during runtime. This is a considerable improvement in comparison to using only offline analysis of worst-case execution times. Self-management Elsevier Worst case execution time analysis Elsevier Distributed computing Elsevier Robot control architecture Elsevier Maaß, Jochen oth Hagner, Matthias oth Steiner, Jens oth Goltz, Ursula oth Raatz, Annika oth Enthalten in Elsevier Discovery of a second generation agonist of the orphan G-protein coupled receptor GPR119 with an improved profile 2012 JSA : the EUROMICRO journal Amsterdam (DE-627)ELV011208724 volume:59 year:2013 number:10 pages:1047-1066 extent:20 https://doi.org/10.1016/j.sysarc.2012.12.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_21 GBV_ILN_22 GBV_ILN_26 GBV_ILN_40 GBV_ILN_70 GBV_ILN_72 GBV_ILN_640 GBV_ILN_2001 GBV_ILN_2002 GBV_ILN_2003 GBV_ILN_2007 46.00 Tiermedizin: Allgemeines VZ AR 59 2013 10 1047-1066 20 045F 004 |
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Enthalten in Discovery of a second generation agonist of the orphan G-protein coupled receptor GPR119 with an improved profile Amsterdam volume:59 year:2013 number:10 pages:1047-1066 extent:20 |
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Discovery of a second generation agonist of the orphan G-protein coupled receptor GPR119 with an improved profile |
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It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across multiple hosts, this article proposes to introduce aspects of self-management into robot control architectures. It is proposed to use graph partitioning algorithms to determine the distribution pattern (mapping of control tasks to CPU resources while minimizing bus communication load). The underlying model and the respective analysis guarantee that, after adaption of the distribution pattern, real-time properties are preserved and load is balanced. In this way, poor a priori assumptions about worst-case execution times are detected and corrected continuously during runtime. This is a considerable improvement in comparison to using only offline analysis of worst-case execution times. |
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It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across multiple hosts, this article proposes to introduce aspects of self-management into robot control architectures. It is proposed to use graph partitioning algorithms to determine the distribution pattern (mapping of control tasks to CPU resources while minimizing bus communication load). The underlying model and the respective analysis guarantee that, after adaption of the distribution pattern, real-time properties are preserved and load is balanced. In this way, poor a priori assumptions about worst-case execution times are detected and corrected continuously during runtime. This is a considerable improvement in comparison to using only offline analysis of worst-case execution times. |
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It can be seen in numerous applications that embedded systems take advantage of distributed execution of tasks. Such distribution is studied in the present article, which investigates the deployment of robot control architectures across multiple computers. Besides the patterns for deployment across multiple hosts, this article proposes to introduce aspects of self-management into robot control architectures. It is proposed to use graph partitioning algorithms to determine the distribution pattern (mapping of control tasks to CPU resources while minimizing bus communication load). The underlying model and the respective analysis guarantee that, after adaption of the distribution pattern, real-time properties are preserved and load is balanced. In this way, poor a priori assumptions about worst-case execution times are detected and corrected continuously during runtime. This is a considerable improvement in comparison to using only offline analysis of worst-case execution times. |
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