计算机应用研究2024，Vol.41Issue(11)：3364-3369,6.DOI:10.19734/j.issn.1001-3695.2024.04.0094
改进的分布估计鲸鱼算法求解区块链DAG任务调度问题
Improved distribution estimation whale algorithm for block chain DAG task scheduling
摘要
Abstract
In order to overcome the efficiency issues of single chain technology in blockchain,a new paradigm directed acyclic graphs is flourishing.This article focused on the non independent task scheduling problem considering cost weights in block-chain directed acyclic graphs,and constructed a mathematical model for task scheduling in blockchain DAG,and proposed a new task scheduling algorithm based on improved distribution estimation whale to solve this problem.The new algorithm intro-duced spatial sampling and statistical learning of EDA in the WO A algorithm to predict the optimal search area,thereby gene-rating excellent new individuals,making the new algorithm have stronger global search ability and faster convergence speed.Finally,through program simulation,it compared the performance of multiple algorithms in terms of convergence speed and glo-bal optimization ability.The experiments show that IEWOA has significant advantages over traditional WO A and EDA in the above parameter performance.In addition,comparing with the improved genetic algorithm FPGA,IEWOA also has certain advantages in parameter performance.关键词
DAG/分布估计/鲸鱼算法/任务调度Key words
DAG/distribution estimation/whale algorithm/task scheduling分类
信息技术与安全科学引用本文复制引用
徐俊,彭俊丰,汤庸,王记红,蔡伟珊..改进的分布估计鲸鱼算法求解区块链DAG任务调度问题[J].计算机应用研究,2024,41(11):3364-3369,6.基金项目
国家自然科学基金资助项目(62306079) （62306079）
广东省教育厅普通高校科研平台和科研项目(2021ZDZX3016) （2021ZDZX3016）
广东第二师范学院校级博士人才科研启动专项资助项目(905001900300200033) （905001900300200033）
广东第二师范学院校级教学质量与教学改革工程项目(2021cyxy02) （2021cyxy02）
广东省教育厅高等教育专项资助项目(2022GXJK287) （2022GXJK287）
