Optimization Method of RTOS System Delay Scheduling Based on Multi-Core Processor

In order to improve the task execution efficiency of multi-core processor, this paper studies the system delay scheduling optimization method of real-time operating system based on multi-core processor. Firstly, the core structure analysis model of multi-core processor data fusion and data acquisition in RTOS system is established, and then the task information flow of delay scheduling in RTOS system is constructed by using the correlation dimension feature fusion method. Based on the power domain non orthogonal multiple access control method, the data fusion state factor of multi-core processor is calculated for the initial scheduling node, and multi-core processor is used to control load balancing in the delay balancing scheduling process of RTOS system, The delay scheduling and balance control of real-time operating system are realized by multi-core processor. Simulation results show that the algorithm has low bit error rate and low task overhead in RTOS system, and can improve the task execution efficiency of multi-core processor.


Introduction
With the explosive growth of intelligent devices, the rise of high-speed services such as augmented reality and virtual reality, and the construction of large-scale equipment of the Internet of things, it is urgent to design efficient and energy-saving communication systems [1] .RTOS system is used to realize green economy and sustainable development.Combined with multi-core processor identification, the delay scheduling model of RTOS system is established.Improve the output balance of real-time operating system.Compared with 4G system, RTOS system realizes 5g communication.The output delay of RTOS system is controlled within 1 ms, and the spectral efficiency is improved by 10 times.Therefore, studying the delay scheduling method of RTOS system is of great significance to improve the output equalization ability of the whole heterogeneous cloud wireless access network [2] .As a distributed and column oriented open source database scheduling problem, the scheduling and transmission of RTOS network task resource platform is the core of data quantization and coding.The quantization and coding of task scheduling data of RTOS system platform are mainly collected by multi-core processor.In the design of task scheduling, we should pay attention to two factors: one is the efficiency of communication coding; The second is the anti-interference performance of the code type after communication coding.In the big data environment of cloud resource platform, how to realize the delay scheduling of RTOS system and the effective coding and quantitative feature fusion of multi-core processor big data is an important problem to solve task scheduling.The traditional methods are not effective in the convergence control and computational overhead control of RTOS system [3] .In addition, when selecting knowledge rules and training samples, it is not necessary to directly use quantum clustering algorithm, but conduct data analysis through path planning and cloud data scheduling, resulting in local distortion and nonlinear deviation of task scheduling [4] .At present, this method can not effectively realize the optimal modeling of delay scheduling execution cost and task scale in RTOS system [5] .To solve the above problems, this paper proposes a delay scheduling algorithm for real-time operating system based on multi-core processor data fusion.In the time delay balancing scheduling process of RTOS system, multi-core processor is used to control load balancing, and pd-noma algorithm is used to improve spectrum efficiency,.The delay scheduling and balance control of real-time operating system are realized by multi-core processor.Finally, the effectiveness and reliability of the algorithm are verified by simulation experiments.
2. Analysis of the data core structure of multi-core processor in TOS system and its problems 2.1.System model and analysis of data core structure of multi-core processor in RTOS system Task scheduling and data fusion technology on Embedded RTOS platform has become a new requirement of network security.The data task scheduling model of multi-core processor in RTOS system is constructed, and the core structure of RTOS system is analyzed.The schematic diagram of RTOS system delay scheduling execution process is shown in Figure 1.

Figure 1. Schematic diagram of delay scheduling execution process of RTOS system
In the process of delay scheduling of RTOS system, the optimal path is selected for route distribution of delay scheduling of RTOS system, and any internal networking node sample is obtained as i x , 1, 2, , i n   , with the characteristic vector as follows: Wherein, the variance of dimension expansion measurement value ) ( ~k w of RTOS system task execution space is ; The covariance between the adjustment fading factor . Assuming that the RTOS system process management processor executes the task, the working state of each RTOS system delay scheduling storage server in the cluster system can be calculated, which can be expressed by a state parameter vector, and the description formula is as follows: w represent the adaptive weight of each task scheduling information flow respectively, i H is the transfer function of anti-interference filtering system, and i V is the attenuation energy in multi-task flow environment.Automatically build Delaunay triangulation network at network nodes, number network nodes and triangles formed, and store the number of network nodes forming each triangle.It is obtained that the number of task arrivals with type 2 ( ) L R is a random parameter.Assuming that the output autocorrelation function of scheduling information in RTOS system platform is dense in Y X  , then the confidence of association rules of scheduling According to the characteristics stored in Voronoi side list, the system model is built and the data fusion kernel of multi-core processor of RTOS system is realized.

Construction and preprocessing of multi-core information flow model
Then, i p is adopted to represent the probability of ( ) x t F appearing in the multi-core processing scheduling interval of RTOS system, and the data exchange sequence of RTOS system task balancing scheduling nodes is as follows: The correlation dimension feature fusion method is used to construct the task information flow of RTOS system delay scheduling, and the quantitative features also contain the random vector with average power of, and the control decomposition result of multi-core processor facing RTOS system is , which is also called interval concept lattice.Is the number of data set X, each element in which is a dimension vector, X contains categories, and the center of the i-th category is , , , , ,  , ) is observed, multiple linear regression analysis is to determine the functional relationship between the value of response variable and the value of forecast variable.
are two loops, and the data updating part is adaptively adjusted by algorithm, and the average execution time in the idle time period of RTOS system delay scheduling is obtained as follows: The kernel structure analysis model of data fusion and data acquisition of multi-core processors in RTOS system is established, and the task information flow of delayed scheduling in RTOS system is constructed by using correlation dimension feature fusion method, and the measurement indexes are obtained.Assuming that the noise ) (k w in the delay scheduling process of RTOS system is between the characteristic vector and the resource scheduling in the imperfect SIC scene, the noise root mean square error correlation function of the wireless access network is obtained, namely: The mean value of the initial state of multi-core processor data fusion is ) 0 ( x , and the variance is 0 x .Based on multi-core processor fusion, the delay scheduling fusion center of RTOS system is independent of . Using the time-frequency feature decomposition relation, according to the error feature matching set of RTOS system delay scheduling, the output threshold function can meet the value of 1 q calculated by 1 1 1 1 1 , thus forming the execution cost interval of embedded task scheduling calculation of RTOS system, namely: Assume that q represents the node positions of multiple task flow sets, all workstations where RTOS system tasks arrive at the sensor nodes to be assigned are running, and the power consumption of BBU pool and the storage space distribution value of baseband signals meet the convergence interval.

Implementation of improved algorithm for data fusion and task scheduling
In order to improve the energy allocation and delay scheduling balance performance of RTOS system, a delay scheduling algorithm of real-time operating system based on multi-core processor data fusion is proposed.The improved design idea and implementation process of the algorithm are as follows: A class of noise-related RTOS system task sensor data fusion system is considered.Assuming that the RTOS system delay scheduling and forecasting information center has obtained the task scheduling command at the moment, the estimated value of RTOS system delay scheduling and forecasting information and the corresponding task scheduling deviation covariance matrix are   , the recursive formula of RTOS system delay scheduling error covariance matrix is calculated as follows: (11) Where I represents the N-order identity matrix, and all embedded task scheduling quantization information of RTOS system at k time is To realize the balanced scheduling of RTOS system delay, a new mapping is formed in the multi-source nodes of RTOS system scheduling tasks: T n x x x x N    (13) Assuming that no new noise correlation is introduced in the quantization process, the final estimated information state of data fusion center of multi-core processor is . By adjusting fading factor, the equalization ability of delay scheduling of RTOS system is improved, and the algorithm is improved.The execution process of the improved RTOS system delay scheduling is shown in Figure 2.

Simulation and result analysis
In order to test the performance of the algorithm in RTOS system delay scheduling, simulation experiments are carried out.The simulation uses TCP / IP system to divide the delay scheduling network system model of RTOS system into seven layers.The hardware environment of the experiment is Dell 2210b, and the processor is Intel Core2 duo1.80GHz, 1G memory.The data set of delay scheduling task in RTOS system is divided into three categories, each of which contains 923, 1000 and 4565 samples respectively.The time series of task scheduling is FM carrier signal with fundamental frequency of 100Hz and FM frequency of 10Hz.According to the above simulation environment and parameter settings, RTOS system network system is used to schedule tasks under Windows system.The time domain waveform simulation of embedded task information flow in RTOS system is shown in Figure 3.
Taking the above task flow sample as the research object, the data fusion and data collection of multi-core processors of RTOS system are carried out, and the core structure analysis and fusion processing of data information flow are carried out.The data fusion algorithm is adopted to realize the fusion tracking of task scheduling sets of RTOS system, and the data fusion results are obtained under different task set N values, as shown in Figure 4.It can be seen from the figure that this algorithm can effectively realize the data fusion processing of RTOS system task information streams with various temporal components, and can clearly obtain the frequency composition of the original multi-core processor data and the dynamic characteristics of its frequency changing with task scheduling, thus realizing task optimization scheduling.In order to compare the performance of the algorithm, this algorithm and the traditional algorithm are adopted, and the comparison result is shown in Figure 5.It can be seen from the figure that this algorithm can effectively improve the execution rate of RTOS system delay scheduling and reduce the execution time.

Figure 5. Comparison of scheduling execution performance
The output bit error rate (BER) is tested, and the comparison results are shown in Table 1.From the analysis of Table 1, it can be seen that the method in this paper has less delay and lower BER when scheduling RTOS system.

Conclusions
This paper presents a delay scheduling optimization method of real-time operating system based on multi-core processor.The core structure analysis model of multi-core processor data fusion and data acquisition in real-time operating system is established.In the case of multi-core processor fusion, the estimated value of RTOS system scheduling task fusion is obtained according to the order of submission time, and the improvement of system delay scheduling algorithm is realized.The results show that this method can improve the execution rate and shorten the execution time of delay scheduling in RTOS system, and has good application value.

Figure 2 .
Figure 2. the execution process of improved RTOS system delay scheduling

Figure 3 .Figure 4 .
Figure 3. Simulation of time domain waveform acquisition by multi-core processor in RTOS system information is the joint cross-correlation function of transactions contained in transaction set.

Table 1 .
Error rate comparison test