基于动态能量感知的移动云计算任务调度模型  

Mobile cloud computing task scheduling model based on dynamic energy aware

作　　者：杨涌 项灵剑 YANG Yong;XIANG Ling-jian(China Mobile Communications Group Zhejiang Co.,Ltd.,Hangzhou 310000,China;Three Dimensional Communication Limited by Share Ltd.,Hangzhou 310000,China)

机构地区：[1]中国移动通信集团浙江有限公司,杭州310000 [2]三维通信股份有限公司,杭州310000

出　　处：《信息技术》2023年第1期73-77,82,共6页Information Technology

摘　　要：传统云计算任务调度忽略了对总完成时间和总能耗目标的加权,导致任务调度的负载均衡性较差。为此,设计基于动态能量感知的移动云计算任务调度模型。将任务调度总完成时间和总能耗作为加权优化目标,引入基于能量感知的多适应度动态遗传算法,求解数学模型。通过遗传算子与再选择策略的相互协作获得新优势种群,并对其更新,寻找最佳移动云计算任务调度结果。实验结果显示,该模型的移动云计算任务调度总完成时间和总能耗较低,具有较好调度效果;负载均衡性良好,可适用于大规模移动云计算任务调度。Traditional cloud computing task scheduling ignores the weighting of the total completion time and total energy consumption, resulting in poor load balancing of task scheduling. Therefore, a task scheduling model of mobile cloud computing based on dynamic energy sensing is designed. Taking the total completion time and total energy consumption of task scheduling as the weighted optimization objectives, a multi-fitness dynamic genetic algorithm based on energy aware is introduced to solve the mathematical model. Through the collaboration of genetic factors and re-selection strategies, a new dominant population is obtained and updated to find the best mobile cloud computing task scheduling results. The experiment results show that the total completion time and total energy consumption of the mobile cloud computing task scheduling model are low, and the scheduling effect is good. The load balancing is good, which is suitable for large-scale mobile cloud computing task scheduling.

关 键 词：动态能量感知 移动云计算 任务调度 新优势种群 多适应度动态遗传算法 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]