Energy-aware Fault-tolerant Scheduling for Hard Real-time Systems

Han, Qiushi

doi:10.25148/etd.fidc000077

Cited by 4 publications

(1 citation statement)

References 118 publications

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“…Faults-tolerant algorithms can be either reactive in the sense they handle the faults only when they occur. Whereas, cognitive algorithms can predict and plan in priori the handling of faults (Kandasamy et al, 2000;Mottaghia & Zarandi, 2014;Han, 2015;Fan & al., 2017;Barkahoum & Hamoudi, 2019). Some typical examples of intelligent RT embedded systems scheduling applications include outpatient clinics (OPCs), smart transport and spacecraft.…”

Section: Real Time Schedulingmentioning

confidence: 99%

AI-Based Methods to Resolve Real-Time Scheduling for Embedded Systems

Boutekkouk

2022

International Journal of Cognitive Informatics and Natural Intelligence

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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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