计算机科学 ›› 2023, Vol. 50 ›› Issue (6A): 220300088-5.doi: 10.11896/jsjkx.220300088
付雄, 房磊, 王俊昌
FU Xiong, FANG Lei, WANG Junchang
摘要： 当前传统的云计算模式已经无法满足用户在低延时场景下的需求,于是移动边缘计算应运而生。为使放置于同一区域内的边缘服务器能够拥有更低的总能耗和均衡的工作负载,提出面向能耗优化和负载均衡的蚁群优化放置算法ACO-ELP(Ant Colony Optimization Energy-consumption Load-balancing Placement)。首先通过构建功耗模型和负载均衡模型,对问题进行定义并将实际参数与算法变量进行对应匹配。在迭代过程中对蚁群算法进行优化,通过动态控制信息素的挥发和留存速率加快算法的迭代速度,同时控制信息素的最大最小值,以确保算法可以尽可能搜索全局最优解,不会陷入局部最优。最后利用上海地区的电信基站数据对算法进行了仿真评估,结果表明与基础放置算法相比,所提算法在减少服务器数量和能耗的同时显著降低了负载偏差值。
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