Optimized scheduling algorithm for soft Real-Time System using particle swarm optimization technique

Teraiya, Jay; Shah, Apurva

doi:10.1007/s12065-021-00599-6

Cited by 16 publications

(8 citation statements)

References 28 publications

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“…While meeting the basic functional requirements, they also need to ensure their safety, reliability and emissions. Therefore, engine fault analysis and diagnosis technology must keep up with the pace of the times to achieve significant development [11][12]. The automobile engine is the necessary equipment to ensure the safe and stable driving of the vehicle, and the fault diagnosis is to analyze the fault inside the whole vehicle body under the condition that the system fully understands the basic conditions.…”

Section: Importance Of Automobile Engine Fault Diagnosismentioning

confidence: 99%

Fusion Particle Swarm Optimization Algorithm in Automobile Engine Fault Diagnosis

2023

KME

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The automobile engine is a high-speed vehicle. Its working principle and process are to generate gas through fuel burning, and then convert the chemical energy contained in the exhaust gas into heat energy. However, in reality, due to various reasons, serious wear and tear inside the engine and sharp reduction of mechanical strength have occurred. This paper mainly introduces a method based on particle swarm optimization algorithm to simplify the complex structure between various systems in the car and outside. The analysis shows that this method has the advantages of accuracy and reliability, and can effectively diagnose and predict it. The advantage of large workload and small space is very prominent. After that, this paper designs a fault diagnosis model of automobile engine based on particle swarm optimization algorithm, and tests the model. The test results show that the fault diagnosis time of this model is short, and the fault diagnosis accuracy is high, which can meet the user needs.

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Section: Importance Of Automobile Engine Fault Diagnosismentioning

confidence: 99%

Fusion Particle Swarm Optimization Algorithm in Automobile Engine Fault Diagnosis

2023

KME

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“…Apart from our research, there are also many other existing solutions available. Some solutions are using EDF algorithm [11,12,15]. Other solutions are based on priorities and/or static scheduling instead of deadlines, which represents less efficient scheduling for RT systems in general [8][9][10][22][23][24][25].…”

Section: Related Workmentioning

confidence: 99%

“…These solutions are not suitable for more complex, robust real-time systems with higher number of tasks and bigger variability of task types. Therefore, a more robust and complex task scheduler with a support of various types of tasks is required [1][2][3][4][5][6][7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

A New FPGA - based Architecture of Task Scheduler with Support of Periodic Real-Time Tasks

Kohútka

2022

2022 29th International Conference on Mixed Design of Integrated Circuits and System (MIXDES)

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This paper presents a new FPGA design of a task scheduler that supports not only aperiodic hard real-time tasks but periodic tasks too. Whenever a period of a periodic task is elapsed, the task is automatically restarted with no need of software intervention. The proposed scheduler is using Earliest Deadline First (EDF) algorithm. For inter-task synchronisation, the scheduler also supports temporary suspension of tasks with automatic resumption of tasks after the specified time elapsed. The proposed architecture is based on priority queues used for time management and decision-making processes. Thanks to FPGA implementation of the scheduler and its priority queues, the scheduler operations are always performed in two clock cycles regardless of the current number of tasks and regardless of the maximum possible number of tasks in the system. The paper contains results obtained by FPGA synthesis done for various parameters using Intel FPGA Cyclone V device. The proposed solution was verified using simplified version of Universal Verification Methodology (UVM) and applying millions of test instructions with randomly generated deadline and period values.

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“…At the same time, a large number of pollutants discharged into rivers and lakes will cause harm to human health and are difficult to degrade. Other pollutants, such as suspended solids and organic matter, will enter the groundwater through surface water to pollute the water quality and worsen the ecological balance of the water body and human health problems [11][12]. At present, the construction of urban sewage treatment plants in China is large in scale and widely distributed.…”

Section: Current Situation Of Water Pollutionmentioning

confidence: 99%

Technical Design of Water Pollution Prevention Project Based on Particle Swarm Optimization

2022

WPPCP

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In the water pollution prevention project, particle swarm optimization is a very practical method, which gathers multiple individuals into a group. It can effectively solve traditional problems. This paper mainly introduces the water pollution control technology and control theory and basic steps based on the characteristics of nuclear particle number and diversity, multi species clustering, etc. Then, it summarizes, analyzes and studies the existing literature on its application and shortcomings, and gives suggestions for improvement. It further explains from the design idea to the algorithm flow, and applies this method to practical projects to reduce costs while ensuring accuracy. Next, based on the research of particle swarm optimization algorithm, this paper designs the technical framework of water pollution prevention and control engineering, and conducts simulation tests on the performance of this algorithm. The test results show that in water pollution prevention and control engineering, through the comparative analysis of the performance of particle swarm optimization algorithm, it is found that the particle swarm optimization algorithm has a fast running time and high iteration efficiency, because it has good global optimization ability, And its performance is also very stable and reliable. Therefore, these factors should be fully considered and utilized in the design process to improve the technical level of water pollution treatment so as to achieve the goal of environmental protection in a real sense.

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Optimized scheduling algorithm for soft Real-Time System using particle swarm optimization technique

Cited by 16 publications

References 28 publications

Fusion Particle Swarm Optimization Algorithm in Automobile Engine Fault Diagnosis

Fusion Particle Swarm Optimization Algorithm in Automobile Engine Fault Diagnosis

A New FPGA - based Architecture of Task Scheduler with Support of Periodic Real-Time Tasks

Technical Design of Water Pollution Prevention Project Based on Particle Swarm Optimization

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