The Method of Real-time Calculation and Scheduling Optimization of Power Data Based on Improved HEFT and Bayesian network
Authors: 
Songhui Zhang, Tao Liu, Xinguang Xu, Tong Cao, Yu Xing, Xianguang DongAuthors Info & Claims
Songhui Zhang, Tao Liu, Xinguang Xu, Tong Cao, Yu Xing, Xianguang DongAuthors Info & ClaimsPages 35 - 40
Abstract
The real-time computing of power data needs to have the ability of a large number of concurrent access services. At present, load balancing technology is mainly used to maximize the computing power support and expansion performance. In order to solve the multi-node dynamic load balancing problem, this paper establishes a load state feedback model based on the improved HEFT(Heterogeneous Earliest Finish Time) algorithmand controls the scheduling results of subsequent tasks by returning their own running state to the scheduler. Then, the Bayesian network model is used to learn the scheduling results, in which a real-time scheduling optimization method based on improved HEFT algorithm and Bayesian network is obtained. Considering the execution authority of different tasks and the interconnection perception between devices, the completion time of the algorithm is significantly better than the existing methods. While solving the scheduling unit overload problem in single scheduling unit system, we solve the equipment conflict problem in multi scheduling unit system. It has certain practical application value for the research of dynamic load balancing problems of real-time calculation of power data.
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Published In
October 2021
182 pages
ISBN:9781450395540
DOI:10.1145/3503181
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Association for Computing Machinery
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Published: 01 March 2022
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ICCSE '21
ICCSE '21: 5th International Conference on Crowd Science and Engineering
October 16 - 18, 2021
Jinan, China
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Overall Acceptance Rate 92 of 247 submissions, 37%
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