Real-time scheduling interfaces and contracts for the design of distributed embedded systems

2013 ◽  
Author(s):  
Ingo Stierand ◽  
Philipp Reinkemeier ◽  
Tayfun Gezgin ◽  
Purandar Bhaduri
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Distributed Embedded Systems ◽  
Real Time Scheduling ◽  
Time Scheduling

A Software Product Line Design Based Approach for Real-time Scheduling of Reconfigurable Embedded Systems

2021 ◽  
Vol 115 ◽  
pp. 104925 ◽  
Author(s):  
Hamza Gharsellaoui ◽  
Jihen Maazoun ◽  
Nadia Bouassida ◽  
Samir Ben Ahmed ◽  
Hanene Ben-Abdallah
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Software Product Line ◽  
Product Line ◽  
Product Line Design ◽  
Real Time Scheduling ◽  
Software Product ◽  
Time Scheduling ◽  
Line Design

scholarly journals AI-based methods to resolve Real time scheduling for embedded systems

2021 ◽  
Vol 15 (4) ◽  
pp. 0-0
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Artificial Immune Systems ◽  
Multi Agent Systems ◽  
Future Directions ◽  
Real Time Scheduling ◽  
Energy Consumption Reduction ◽  
Consumption Reduction ◽  
Time Scheduling ◽  
Multi Agent

Artificial Intelligence is becoming more attractive to resolve nontrivial problems including the well known real time scheduling (RTS) problem for Embedded Systems (ES). The latter is considered as a hard multi-objective optimization problem because it must optimize at the same time three key conflictual objectives that are tasks deadlines guarantee, energy consumption reduction and reliability enhancement. In this paper, we firstly present the necessary background to well understand the problematic of RTS in the context of ES, then we present our enriched taxonomies for real time, energy and faults tolerance aware scheduling algorithms for ES. After that, we survey the most pertinent existing works of literature targeting the application of AI methods to resolve the RTS problem for ES notably Constraint Programming, Game theory, Machine learning, Fuzzy logic, Artificial Immune Systems, Cellular Automata, Evolutionary algorithms, Multi-agent Systems and Swarm Intelligence. We end this survey by a discussion putting the light on the main challenges and the future directions.

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