Real-Time Scheduling and Schedulability Analysis

2003 ◽  
pp. 41-85
Keyword(s):  
Real Time ◽  
Schedulability Analysis ◽  
Real Time Scheduling ◽  
Time Scheduling

Schedulability Analysis for Timed Automata With Tasks

2021 ◽  
Vol 20 (5s) ◽  
pp. 1-26
Author(s):  
Jinghao Sun ◽  
Nan Guan ◽  
Rongxiao Shi ◽  
Guozhen Tan ◽  
Wang Yi
Keyword(s):  
Model Checking ◽  
State Space ◽  
Real Time ◽  
Timed Automata ◽  
Schedulability Analysis ◽  
Scheduling Theory ◽  
Real Time Scheduling ◽  
Analysis Techniques ◽  
Model Complex ◽  
Time Scheduling

Research on modeling and analysis of real-time computing systems has been done in two areas, model checking and real-time scheduling theory. In model checking, an expressive modeling formalism such as timed automata (TA) is used to model complex systems, but the analysis is typically very expensive due to state-space explosion. In real-time scheduling theory, the analysis techniques are highly efficient, but the models are often restrictive. In this paper, we aim to exploit the possibility of applying efficient analysis techniques rooted in real-time scheduling theory to analysis of real-time task systems modeled by timed automata with tasks (TAT). More specifically, we develop efficient techniques to analyze the feasibility of TAT-based task models (i.e., whether all tasks can meet their deadlines on single-processor) using demand bound functions (DBF), a widely used workload abstraction in real-time scheduling theory. Our proposed analysis method has a pseudo-polynomial time complexity if the number of clocks used to model each task is bounded by a constant, which is much lower than the exponential complexity of the traditional model-checking based analysis approach (also assuming the number of clocks is bounded by a constant). We apply dynamic programming techniques to implement the DBF-based analysis framework, and propose state space pruning techniques to accelerate the analysis process. Experimental results show that our DBF-based method can analyze a TAT system with 50 tasks within a few minutes, which significantly outperforms the state-of-the-art TAT-based schedulability analysis tool TIMES.

Workload assignment for global real-time scheduling on unrelated clustered platforms

2021 ◽  
Author(s):  
Antoine Bertout ◽  
Joël Goossens ◽  
Emmanuel Grolleau ◽  
Roy Jamil ◽  
Xavier Poczekajlo
Keyword(s):  
Real Time ◽  
Real Time Scheduling ◽  
Time Scheduling

scholarly journals Research on Multi-Timescale Coordinated Method for Source-Grid-Load with Uncertain Renewable Energy Considering Demand Response

2021 ◽  
Vol 13 (6) ◽  
pp. 3400
Author(s):  
Jia Ning ◽  
Sipeng Hao ◽  
Aidong Zeng ◽  
Bin Chen ◽  
Yi Tang
Keyword(s):  
Renewable Energy ◽  
Real Time ◽  
Demand Response ◽  
System Operation ◽  
Real Time Scheduling ◽  
High Penetration ◽  
Time Scheduling ◽  
Grid Load ◽  
Grid Side ◽  
Scheduling Models

The high penetration of renewable energy brings great challenges to power system operation and scheduling. In this paper, a multi-timescale coordinated method for source-grid-load is proposed. First, the multi-timescale characteristics of wind forecasting power and demand response (DR) resources are described, and the coordinated framework of source-grid-load is presented under multi-timescale. Next, economic scheduling models of source-grid-load based on multi-timescale DR under network constraints are established in the process of day-ahead scheduling, intraday scheduling, and real-time scheduling. The loads are classified into three types in terms of different timescale. The security constraints of grid side and time-varying DR potential are considered. Three-stage stochastic programming is employed to schedule resources of source side and load side in day-ahead, intraday, and real-time markets. The simulations are performed in a modified Institute of Electrical and Electronics Engineers (IEEE) 24-node system, which shows a notable reduction in total cost of source-grid-load scheduling and an increase in wind accommodation, and their results are proposed and discussed against under merely two timescales, which demonstrates the superiority of the proposed multi-timescale models in terms of cost and demand response quantity reduction.

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