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Multicycle polling scheduling algorithms for FieldBus networks

REAL-TIME SYSTEMS 2003年第2-3期25卷 157-185页

作者： Cavalieri, S Monforte, S Corsaro, A Scapellato, G Univ Catania Fac Engn Dept Comp Sci & Telecommun Engn I-95125 Catania Italy Univ Calif Irvine Dept Elect & Comp Engn Irvine CA 92697 USA Ericsson Lab Italy I-00040 Rome Italy

The paper deals with the scheduling of periodic information flow in a FieldBus environment. The scheduling problem is defined from an analytical point of view, giving a brief survey of the most well-known solutions. One of these is called multicycle polling scheduling, which is based on the hypothesis that all the production periods of the periodic processes to be scheduled are harmonic. Although in some process control or manufacturing scenarios, this hypothesis may be acceptable, there are many real industrial processes to which it cannot be applied. The aim of the paper is to make a contribution towards solving the scheduling problem. It essentially concerns extension of the theory on which multicycle polling scheduling is based to a much more realistic and general scenario, where the periods of all the processes to be scheduled have arbitrary values. The authors present a new formulation of multicycle polling scheduling, called extended multicycle polling scheduling, and demonstrate that it comprises the scenario currently considered in the literature. Two algorithmic solutions for extended multicycle polling scheduling are then proposed, giving a computational complexity analysis which will highlight the capability of the algorithmic scheduling solutions to be performed on-line. The paper concludes by comparing the multicycle polling scheduling approach known in literature and the one presented in the paper. Comparison is performed by evaluating the use of available bandwidth to serve both periodic and asynchronous traffic in the two approaches.

关键词： FieldBus communication networks hard real-time scheduling priority scheduling algorithm rate monotonic algorithm earliest deadline first algorithm

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Scheduling algorithms for Real Time Operating Systems in Space Domain 5

Scheduling Algorithms for Real Time Operating Systems in Spa...

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5th International Conference on Computer Science and Engineering (UBMK)

作者： Kutlu, Ezgi Gencturk, Camal Turk Havacilik & Uzay Sanayii AS Uzay Sistemleri Yazilim Muhendisligi Ankara Turkey

ISBN: (纸本)9781728175652

Time-critical requirements of real time systems are provided by software applications running on real time operating systems. These software tasks must be scheduled based on software and hardware events. There are some services (priority based preemption etc.) in real time operating systems to control software tasks. But in some situations there is a need for scheduling algorithms in real time systems. This need arises especially when time-critical software tasks need to run at different working periods and on a specific timeline. Different scheduling algorithms can be selected to meet the requirements of the system. The flight software that runs on the real-time operating system, especially on satellite platforms, is responsible for time-critical tasks. Main goals of this paper are providing analyze of scheduling algorithms using in real time operating systems, giving the method which is used to apply scheduling algorithms in a real time operating system and providing performance results of these scheduling algorithms obtained as a result of this application. In addition, it is mentioned that which of these algorithms are preferred in space domain.

关键词： Space Domain Operating System Task Scheduling algorithms Round Robin algorithm Rate Monotonic algorithm deadline Monotonic algorithm earliest deadline first algorithm Least Laxity first algorithm Enhanced Least Laxity first algorithm

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Almost sure exponential stability of stochastic nonlinear semi-Markov jump T-S fuzzy systems under intermittent EDF scheduling controller

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JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2024年第17期361卷

作者： Zhu, Dalin Zhu, Quanxin Hunan Normal Univ Sch Math & Stat MOE LCSM CHP LCOCS Changsha 410081 Hunan Peoples R China

This paper studies the almost sure exponential stability (ASES) with a random switching process of stochastic nonlinear semi-Markov jump T-S Fuzzy systems (SMJT-SFSs) based on an intermittent scheduling controller. The intermittent scheduling controller is established by the earliest deadline first (EDF) algorithm, where the controller is enabled to take a rest interval. By building a mode-dependent Lyapunov function and employing the It & ocirc;formula, the sufficient stability conditions of the SMJT-SFSs with intermittent scheduling controller are obtained about solvable forms of linear matrix inequalities (LMIs). Furthermore, we explore two special cases involving linear systems and deterministic systems. In addition, an application example of the nonlinear robot arm model of single-link is provided to illustrate the results.

关键词： Almost sure exponential stability Semi-Markov jump T-S Fuzzy systems Intermittent scheduling controller earliest deadline first algorithm Linear matrix inequalities

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A Framework for Real-Time Information Derivation from Big Sensor Data

A Framework for Real-Time Information Derivation from Big Se...

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IEEE International Symposium on Cyberspace Safety and Security

作者： Liehuo Chen Kyoung-Don Kang Dept. of Comput. Sci. State Univ. of New York at Binghamton Binghamton NY USA

ISBN: (纸本)9781479989386

In data-intensive real-time applications, e.g., transportation management and location-based services, the amount of sensor data is exploding. In these applications, it is desirable to extract value-added information, e.g., fast driving routes, from sensor data streams in real-time rather than overloading users with massive raw data. However, achieving the objective is challenging due to the data volume and complex data analysis tasks with stringent timing constraints. Most existing big data management systems, e.g., Hadoop, are not directly applicable to real-time sensor data analytics, since they are timing agnostic and focus on batch processing of previously stored data that are potentially outdated and subject to I/O overheads. To address the problem, we design a new real-time big data management framework, which supports a non-preemptive periodic task model for continuous in-memory sensor data analysis and a schedulability test based on the EDF (earliest deadline first) algorithm to derive information from current sensor data in real-time by extending the map-reduce model originated in functional programming. As a proof-of-concept case study, a prototype system is implemented. In the performance evaluation, it is empirically shown that all deadlines can be met for the tested sensor data analysis benchmarks.

关键词： Big Data batch processing (computers) data analysis functional programming parallel processing performance evaluation EDF algorithm I/O overheads batch processing complex data analysis tasks continuous in-memory sensor data analysis data volume data-intensive real-time applications earliest deadline first algorithm nonpreemptive periodic task model real-time big data management framework real-time information derivation real-time sensor big data analytics schedulability test stringent timing constraints timing agnostic value-added information extraction Analytical models Big data Data analysis Data models Mobile radio mobility management Real-time systems Timing Big Sensor Data Real-Time Information

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