Adaptive Exchange of Distributed Partial ...
Document type :
Communication dans un congrès avec actes
Title :
Adaptive Exchange of Distributed Partial Models@run.time for Highly Dynamic Systems
Author(s) :
Gotz, Sebastian [Auteur]
Technische Universität Dresden = Dresden University of Technology [TU Dresden]
Gerostathopoulos, Ilias [Auteur]
Univerzita Karlova [Praha, Česká republika] = Charles University [Prague, Czech Republic] [UK]
Krikava, Filip [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Shahzada, Adnan [Auteur]
Politecnico di Milano [Milan] [POLIMI]
Spalazzese, Romina [Auteur]
Malmö Högskola = Malmö University
Technische Universität Dresden = Dresden University of Technology [TU Dresden]
Gerostathopoulos, Ilias [Auteur]
Univerzita Karlova [Praha, Česká republika] = Charles University [Prague, Czech Republic] [UK]
Krikava, Filip [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Shahzada, Adnan [Auteur]
Politecnico di Milano [Milan] [POLIMI]
Spalazzese, Romina [Auteur]
Malmö Högskola = Malmö University
Conference title :
Proceedings of 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems
City :
Firenze
Country :
Italie
Start date of the conference :
2015-05-18
HAL domain(s) :
Informatique [cs]/Génie logiciel [cs.SE]
Informatique [cs]/Recherche d'information [cs.IR]
Informatique [cs]/Recherche d'information [cs.IR]
English abstract : [en]
We are experiencing a world where Cyber-Physical Systems (CPSs) play a more and more crucial role. CPSs integrate computational, physical, and networking elements; they comprise a number of subsystems, or entities, that ...
Show more >We are experiencing a world where Cyber-Physical Systems (CPSs) play a more and more crucial role. CPSs integrate computational, physical, and networking elements; they comprise a number of subsystems, or entities, that are connected and work together. The open and highly distributed nature of the resulting system gives rise to unanticipated runtime management issues such as the organization of subsystems and resource optimization.In this paper, we focus on the problem of knowledge sharing among cooperating entities of a highly distributed and self- adaptive CPS. Specifically, the research question we address is how to minimize the knowledge that needs to be shared among the entities of a CPS. If all entities share all their knowledge with each other, the performance, energy and memory consumption as well as privacy are unnecessarily negatively impacted. To reduce the amount of knowledge to share between CPS entities, we envision a role-based adaptive knowledge exchange technique working on partial runtime models, i.e., models reflecting only part of the state of the CPS. Our approach supports two adaptation dimensions: the runtime type of and conditions over the knowledge. We illustrate the feasibility of our technique by discussing its realization based on two state-of-the-art approaches.Show less >
Show more >We are experiencing a world where Cyber-Physical Systems (CPSs) play a more and more crucial role. CPSs integrate computational, physical, and networking elements; they comprise a number of subsystems, or entities, that are connected and work together. The open and highly distributed nature of the resulting system gives rise to unanticipated runtime management issues such as the organization of subsystems and resource optimization.In this paper, we focus on the problem of knowledge sharing among cooperating entities of a highly distributed and self- adaptive CPS. Specifically, the research question we address is how to minimize the knowledge that needs to be shared among the entities of a CPS. If all entities share all their knowledge with each other, the performance, energy and memory consumption as well as privacy are unnecessarily negatively impacted. To reduce the amount of knowledge to share between CPS entities, we envision a role-based adaptive knowledge exchange technique working on partial runtime models, i.e., models reflecting only part of the state of the CPS. Our approach supports two adaptation dimensions: the runtime type of and conditions over the knowledge. We illustrate the feasibility of our technique by discussing its realization based on two state-of-the-art approaches.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
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