Energy-Aware Non-Preemptive Scheduling of Mixed-Criticality Real-Time Task Systems

2021 ◽  
pp. 1-1
Author(s):  
Yi-Wen Zhang
Keyword(s):  
Real Time ◽  
Preemptive Scheduling ◽  
Energy Aware ◽  
Time Task ◽  
Task Systems ◽  
Mixed Criticality

scholarly journals Contention & Energy-Aware Real-Time Task Mapping on NoC Based Heterogeneous MPSoCs

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 75110-75123 ◽  
Author(s):  
Haider Ali ◽  
Umair Ullah Tariq ◽  
Yongjun Zheng ◽  
Xiaojun Zhai ◽  
Lu Liu
Keyword(s):  
Real Time ◽  
Task Mapping ◽  
Energy Aware ◽  
Time Task

Efficient Feasibility Analysis for Graph-Based Real-Time Task Systems

2020 ◽  
Vol 39 (11) ◽  
pp. 3385-3397
Author(s):  
Jinghao Sun ◽  
Rongxiao Shi ◽  
Kexuan Wang ◽  
Nan Guan ◽  
Zhishan Guo
Keyword(s):  
Real Time ◽  
Feasibility Analysis ◽  
Time Task ◽  
Task Systems

scholarly journals Towards Fully Jitterless Applications: Periodic Scheduling in Multiprocessor MCSs Using a Table-Driven Approach

2020 ◽  
Vol 10 (19) ◽  
pp. 6702
Author(s):  
Eugenia Ana Capota ◽  
Cristina Sorina Stangaciu ◽  
Mihai Victor Micea ◽  
Daniel-Ioan Curiac
Keyword(s):  
Real Time ◽  
Multiprocessor Systems ◽  
Preemptive Scheduling ◽  
Algorithm Performance ◽  
Safety Critical ◽  
Time Table ◽  
Scheduling Method ◽  
Embedded Applications ◽  
Special Case ◽  
Mixed Criticality

In mixed criticality systems (MCSs), the time-triggered scheduling approach focuses on a special case of safety-critical embedded applications which run in a time-triggered environment. Sometimes, for these types of MCSs, perfectly periodical (i.e., jitterless) scheduling for certain critical tasks is needed. In this paper, we propose FENP_MC (Fixed Execution Non-Preemptive Mixed Criticality), a real-time, table-driven, non-preemptive scheduling method specifically adapted to mixed criticality systems which guarantees jitterless execution in a mixed criticality time-triggered environment. We also provide a multiprocessor version, namely, P_FENP_MC (Partitioned Fixed Execution Non-Preemptive Mixed Criticality), using a partitioning heuristic. Feasibility tests are proposed for both uniprocessor and homogenous multiprocessor systems. An analysis of the algorithm performance is presented in terms of success ratio and scheduling jitter by comparing it against a time-triggered and an event-driven method in a non-preemptive context.

Optimized Slowdown in Real-Time Task Systems

2006 ◽  
Vol 55 (12) ◽  
pp. 1588-1598 ◽  
Author(s):  
R. Jejurikar ◽  
R. Gupta
Keyword(s):  
Real Time ◽  
Time Task ◽  
Task Systems

On the Scheduling of Mixed-Criticality Real-Time Task Sets

2009 ◽  
Author(s):  
Dionisio de Niz ◽  
Karthik Lakshmanan ◽  
Ragunathan Rajkumar
Keyword(s):  
Real Time ◽  
Time Task ◽  
Task Sets ◽  
Mixed Criticality

scholarly journals Energy-Aware Real-Time Task Scheduling for Heterogeneous Multiprocessors with Particle Swarm Optimization Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Weizhe Zhang ◽  
Hucheng Xie ◽  
Boran Cao ◽  
Albert M. K. Cheng
Keyword(s):  
Particle Swarm Optimization ◽  
Energy Consumption ◽  
Real Time ◽  
Task Scheduling ◽  
Particle Swarm ◽  
Energy Aware ◽  
Swarm Optimization ◽  
Heterogeneous Multiprocessors ◽  
Time Task ◽  
Feasible Solutions

Energy consumption in computer systems has become a more and more important issue. High energy consumption has already damaged the environment to some extent, especially in heterogeneous multiprocessors. In this paper, we first formulate and describe the energy-aware real-time task scheduling problem in heterogeneous multiprocessors. Then we propose a particle swarm optimization (PSO) based algorithm, which can successfully reduce the energy cost and the time for searching feasible solutions. Experimental results show that the PSO-based energy-aware metaheuristic uses 40%–50% less energy than the GA-based and SFLA-based algorithms and spends 10% less time than the SFLA-based algorithm in finding the solutions. Besides, it can also find 19% more feasible solutions than the SFLA-based algorithm.

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