Dynamic optimization of load balancing for streaming server clusters based on LAE-KNN

Nengwu Liu; Shuming Jiang; Guoli Yang

doi:10.1117/12.2671079

28 April 2023 Dynamic optimization of load balancing for streaming server clusters based on LAE-KNN

Nengwu Liu, Shuming Jiang, Guoli Yang

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126103C (2023) https://doi.org/10.1117/12.2671079
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

In order to improve the timeliness of load feedback of streaming media cluster nodes and the processing efficiency of multiple concurrent requests, an improved algorithm based on dynamic feedback is proposed. The optimization of the method is as follows: (1) The calculation method of the load index weight coefficient and load weight value is improved, where the Least Squares is used to combine the optimization Analysis Hierarchy Process and Entropy Weight Method (denoted as LAE), which combine subjective weighting and objective weighting; (2) The feedback period is dynamically modified by the change in the number of tasks of the cluster nodes; (3) The Euclidean distance of the KNN algorithm is changed to a weighted Euclidean distance based on the weights obtained in (1). The cluster nodes are classified according to the improved KNN algorithm (denoted as LAE-KNN) and the load information, and the tasks are assigned to the class with the smallest total weight ratio; (4) At the same time, load migration is realized by setting the threshold of the load index, and random tasks of nodes exceeding the threshold of the load index are redirected to the low-load class according to the load information in each feedback cycle, to improve the load balancing effect of the cluster. Experiments show that the algorithm can effectively solve the problem of cluster load skew caused by many concurrent requests and can improve the load balancing effect of streaming media clusters.

Citation Download Citation

Nengwu Liu, Shuming Jiang, and Guoli Yang "Dynamic optimization of load balancing for streaming server clusters based on LAE-KNN", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126103C (28 April 2023); https://doi.org/10.1117/12.2671079

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