Task Scheduling Algorithm Of Cyber-Physical System Base On Complex Industry And Big Data

With the rapid development of distributed,big data,cloud computing and other information technologies,as well as sensors and embedded hardware technologies,CPS technology has a variety of solutions to solve the problems of practical application scenarios in industry.In the complex industry,the task scheduling process of the CPS system under big data is prone to unbalanced system load due to high data concurrency,heterogeneous resources,and complex task nature.As a result,the load accumulated during the task scheduling process cannot be balanced due to the increase in load accumulated by the task amount The system is down.Even though there are many cloud computing scheduling algorithms that can solve the load balancing problem in distributed cluster systems well,the complex factors in the specific situation of the CPS system,scheduling algorithms that only consider the system load or only consider the attributes of tasks are still prone to appear The unstable state of the system causes the overall efficiency of scheduling to drop.In view of the above problems,this paper considers and studies from the overall perspective of the system,and at the same time considers the impact of system load and task attributes on task scheduling,proposes a performance index to regulate the system load and task execution status to ensure that the system performs tasks in the best state Under the premise of,the task scheduling scheme to reduce the risk of the system in an unstable state in a timely manner.It includes the following aspects:1.In-depth understanding of the background of the CPS system task scheduling algorithm,such as cloud computing,big data,and analyze its characteristics.The current development status of task scheduling,analyze the advantages and disadvantages of various algorithms.2.Study the principle of queuing theory,analyze the composition of different queuing models,and select the queuing model that conforms to the CPS system structure in complex industry as the running scenario of the scheduling algorithm proposed in this paper.Study and analyze the calculation method and correlation of each index parameter under the model,and systematically model the queuing model.Combined with the queuing theory,a dynamic feedback CPS task scheduling strategy model based on queuing theory is proposed(Queuing Theory Task Scheduling).After quantitative analysis,in order to optimize the deficiencies of the algorithm in certain aspects and improve the efficiency of the CPS system for scheduling tasks of different values,a fusion of multi-level priority ranking algorithm based on task service value and task feedback scheduling algorithm is proposed to further improve the scheduling algorithm Performance and fitness.3.This paper uses the Cloud Sim Toolkit 3.0 cloud computing simulation platform to perform simulation experiments on the scheduling algorithm in this paper.The experimental results prove that the proposed scheduling algorithm theory in this paper is faster in task response time,stronger load balancing ability,and more effective The high efficiency of task value scheduling demonstrates the feasibility and operational performance of the scheduling strategy proposed in this paper,and finally summarizes the advantages and disadvantages of the algorithm,as well as the next research direction.