Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Internet and Distributed Computing Systems |
| Untertitel | 8th International Conference, IDCS 2015, Proceedings |
| Herausgeber/-innen | Giuseppe Di Fatta, Mukaddim Pathan, Giancarlo Fortino, Antonio Guerrieri, Frederic Stahl, Wenfeng Li |
| Herausgeber (Verlag) | Springer Verlag |
| Seiten | 103-117 |
| Seitenumfang | 15 |
| ISBN (Print) | 9783319232362 |
| Publikationsstatus | Veröffentlicht - 25 Aug. 2015 |
| Veranstaltung | 8th International Conference on Internet and Distributed Computing Systems, IDCS 2015 - Windsor, Großbritannien / Vereinigtes Königreich Dauer: 2 Sept. 2015 → 4 Sept. 2015 |
Publikationsreihe
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Band | 9258 |
| ISSN (Print) | 0302-9743 |
| ISSN (elektronisch) | 1611-3349 |
Abstract
This paper presents a holistic approach to execute tasks in distributed smart systems. This is shown by the example of monitoring tasks in smart camera networks. The proposed approach is general and thus not limited to a specific scenario. A job-resource model is introduced to describe the smart system and the tasks, with as much order as necessary and as few rules as possible. Based on that model, a local algorithm is presented, which is developed to achieve optimization transparency. This means that the optimization on system-wide criteria will not be visible to the participants. To a task, the system-wide optimization is a virtual local single-step optimization. The algorithm is based on proactive quotation broadcasting to the local neighborhood. Additionally, it allows the parallel execution of tasks on resources and includes the optimization of multiple-task-to-resource assignments.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Theoretische Informatik
- Informatik (insg.)
- Allgemeine Computerwissenschaft
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- BibTex
- RIS
Internet and Distributed Computing Systems : 8th International Conference, IDCS 2015, Proceedings. Hrsg. / Giuseppe Di Fatta; Mukaddim Pathan; Giancarlo Fortino; Antonio Guerrieri; Frederic Stahl; Wenfeng Li. Springer Verlag, 2015. S. 103-117 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 9258).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Task execution in distributed smart systems
AU - Jänen, Uwe
AU - Grenz, Carsten
AU - Edenhofer, Sarah
AU - Stein, Anthony
AU - Brehm, Jürgen
AU - Hähner, Jörg
PY - 2015/8/25
Y1 - 2015/8/25
N2 - This paper presents a holistic approach to execute tasks in distributed smart systems. This is shown by the example of monitoring tasks in smart camera networks. The proposed approach is general and thus not limited to a specific scenario. A job-resource model is introduced to describe the smart system and the tasks, with as much order as necessary and as few rules as possible. Based on that model, a local algorithm is presented, which is developed to achieve optimization transparency. This means that the optimization on system-wide criteria will not be visible to the participants. To a task, the system-wide optimization is a virtual local single-step optimization. The algorithm is based on proactive quotation broadcasting to the local neighborhood. Additionally, it allows the parallel execution of tasks on resources and includes the optimization of multiple-task-to-resource assignments.
AB - This paper presents a holistic approach to execute tasks in distributed smart systems. This is shown by the example of monitoring tasks in smart camera networks. The proposed approach is general and thus not limited to a specific scenario. A job-resource model is introduced to describe the smart system and the tasks, with as much order as necessary and as few rules as possible. Based on that model, a local algorithm is presented, which is developed to achieve optimization transparency. This means that the optimization on system-wide criteria will not be visible to the participants. To a task, the system-wide optimization is a virtual local single-step optimization. The algorithm is based on proactive quotation broadcasting to the local neighborhood. Additionally, it allows the parallel execution of tasks on resources and includes the optimization of multiple-task-to-resource assignments.
KW - Job-resource-model
KW - Multiple-task-to-resource assignment
KW - Optimization transparency
KW - Proactive quotation-based optimization
KW - Virtual local single-step optimization
UR - http://www.scopus.com/inward/record.url?scp=84945570936&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-23237-9_10
DO - 10.1007/978-3-319-23237-9_10
M3 - Conference contribution
AN - SCOPUS:84945570936
SN - 9783319232362
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 103
EP - 117
BT - Internet and Distributed Computing Systems
A2 - Di Fatta, Giuseppe
A2 - Pathan, Mukaddim
A2 - Fortino, Giancarlo
A2 - Guerrieri, Antonio
A2 - Stahl, Frederic
A2 - Li, Wenfeng
PB - Springer Verlag
T2 - 8th International Conference on Internet and Distributed Computing Systems, IDCS 2015
Y2 - 2 September 2015 through 4 September 2015
ER -