Temperature-aware Task Partitioning for Real-Time Scheduling in Embedded Systems

2012 ◽  
Author(s):  
Zhe Wang ◽  
Sanjay Ranka ◽  
Prabhat Mishra
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Task Partitioning ◽  
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 Energy-Efficient Task Partitioning for Real-Time Scheduling on Multi-Core Platforms

Computers ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 10
Author(s):  
Manal A. El Sayed ◽  
El Sayed M. Saad ◽  
Rasha F. Aly ◽  
Shahira M. Habashy
Keyword(s):  
Energy Consumption ◽  
Real Time ◽  
Bin Packing ◽  
Shared Resources ◽  
Energy Aware ◽  
Task Partitioning ◽  
Worst Case ◽  
Real Time Scheduling ◽  
Static Partitioning ◽  
Time Scheduling

Multi-core processors have become widespread computing engines for recent embedded real-time systems. Efficient task partitioning plays a significant role in real-time computing for achieving higher performance alongside sustaining system correctness and predictability and meeting all hard deadlines. This paper deals with the problem of energy-aware static partitioning of periodic, dependent real-time tasks on a homogenous multi-core platform. Concurrent access of the tasks to shared resources by multiple tasks running on different cores induced a higher blocking time, which increases the worst-case execution time (WCET) of tasks and can cause missing the hard deadlines, consequently resulting in system failure. The proposed blocking-aware-based partitioning (BABP) algorithm aims to reduce the overall energy consumption while avoiding deadline violations. Compared to existing partitioning strategies, the proposed technique achieves more energy-saving. A series of experiments test the capabilities of the suggested algorithm compared to popular heuristics partitioning algorithms. A comparison was made between the most used bin-packing algorithms and the proposed algorithm in terms of energy consumption and system schedulability. Experimental results demonstrate that the designed algorithm outperforms the Worst Fit Decreasing (WFD), Best Fit Decreasing (BFD), and Similarity-Based Partitioning (SBP) algorithms of bin-packing algorithms, reduces the energy consumption of the overall system, and improves schedulability.

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.

Real-Time Scheduling for Embedded Systems

2005 ◽  
pp. 173-195 ◽  
Author(s):  
Marco Caccamo ◽  
Theodore Baker ◽  
Alan Burns ◽  
Giorgio Buttazzo ◽  
Lui Sha
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Real Time Scheduling ◽  
Time Scheduling
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