计算机与数字工程2019，Vol.47Issue(3)：524-529,6.DOI:10.3969/j.issn.1672-9722.2019.03.008
面向电能质量数据采集的蚁群优化算法
Ant Colony Optimization Algorithm for Power Quality Data Acquisition
王嘉怡 1房俊 2高鹏1
作者信息
- 1. 北方工业大学大规模流数据集成与分析技术北京市重点实验室 北京 100144
- 2. 北方工业大学数据工程研究院 北京 100144
- 折叠
摘要
Abstract
The data existing collection of the power grid adopts centralized or single-node mode. The acquisition efficiency of these two methods is low,which is difficult to meet the acquisition requirement of massive power quality data. Based on the charac?teristics of power quality data,this paper extends data reception processing node and proposes a task scheduling optimization based on ant colony algorithm for grid power quality data acquisition,and realizes server load balancing to improve data collection efficien?cy. The experimental results show that the scheduling speed of the ant colony optimization algorithm is about 2.65 times of that of the existing data scheduling method,and the data distribution ratio of each receiving server is basically maintained at 0.3~0.4. The ant colony optimization algorithm reduces the randomness of the task allocation when the server load difference is small. The allocation ratio is close to 1:1:1. When the server load difference is large,the probability of allocating a single node in the task is reduced. The optimal range of the combination of the relevant parameters of the ant colony optimization algorithm is found,and the average time of the task is reduced about 3.7. The feasibility and validity of the ant colony optimization algorithm are verified by experiments.关键词
蚁群算法/负载均衡/任务调度/HBaseKey words
ant colony algorithm/load balancing/task scheduling/HBase分类
信息技术与安全科学引用本文复制引用
王嘉怡,房俊,高鹏..面向电能质量数据采集的蚁群优化算法[J].计算机与数字工程,2019,47(3):524-529,6.
