Cross-source Scheduling Method of Computer Heterogeneous Big Data Based on Heuristic Algorithm
In order to improve the performance of cross-source scheduling of computer heterogeneous big data,a cross-source scheduling method of computer heterogeneous big data based on heuristic algorithm is proposed.The cross-source scheduling task of computer heterogeneous big data is divided into several subtasks,and a time load balancing model of cross-source scheduling is constructed by using max-min thought and min-max thought.Based on the flexibility of cross-source scheduling order of computer heterogeneous big data,the optimal scheduling task is selected by using the optimal strategy of heuristic algorithm.According to the state of computer heterogeneous big data,the throughput of heterogeneous big data transmission control protocol connection is calculated,and the quality of heterogeneous big data to be scheduled is taken as the sub-stream weight of computer data layer,and cross-source scheduling of computer heterogeneous big data is realized by processing all sub-streams to be scheduled.The experimental results show that the method can improve the level condition of cross-source operation to 10,the utilization rate of heterogeneous big data exceeds 97%,and the acceleration ratio is more than 85%,which improves the performance of heterogeneous big data.
heuristic algorithmcomputerscheduling taskscross-source schedulingload balancingheterogeneous big data
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