海洋开发与管理2023，Vol.40Issue(11)：31-36,6.
基于竞争遗传算法的海洋云平台资源调度模型研究
Research on Resource Scheduling Model of Ocean Cloud Platform Based on Competitive Genetic Algorithm
摘要
Abstract
High quality marine natural resource management cannot be achieved without the sup-port of data and information.Given the unique nature of marine data,the processing of marine environmental data often involves long time series or large-scale processing work.For data pro-cessing work mainly focused on intensive computing,universal cloud platforms have prominent issues of low efficiency.Based on a comprehensive analysis of the native resource scheduling al-gorithms on the Hadoop platform and the characteristics of intensive computing in ocean data processing,this paper innovatively proposes a genetic algorithm task scheduling strategy based on a competitive model.The use of chaotic algorithm mechanism as the basis for genetic algo-rithm population initialization ensures that the solution space obtained during each initialization can be uniformly distributed,effectively solving the problem of genetic algorithm solving speed being greatly affected by the initialization population and population evolution measurement.In addition,in order to speed up rate of convergence,competition mechanism is introduced and an adaptive evolution model based on population competition is proposed.Through the actual veri-fication and comparison of the built models,it is proved that the improved algorithm is superior to the traditional genetic algorithm in rate of convergence and stability of the convergence re-sults,and has greatly improved the ability and efficiency of improving the resource scheduling of the ocean cloud platform.关键词
海洋数据处理/云计算/遗传算法/CloudSim/任务调度Key words
Ocean data processing/Cloud computing/Cloud services/CloudSim/Task schedu-ling分类
海洋科学引用本文复制引用
王烨嘉,王蕾,陈竹,周海英..基于竞争遗传算法的海洋云平台资源调度模型研究[J].海洋开发与管理,2023,40(11):31-36,6.基金项目
广东省产业集群研究 （）
广东省海洋经济发展(海洋六大产业)专项资金项目"粤港澳大湾区现代海洋产业体系融合发展研究"(粤自然合[2023]44号). （海洋六大产业）
