摘要
移动边缘计算(MEC)通过将计算中心下沉至网络边缘,可以有效服务于任务计算.然而,MEC拥有的计算资源并不是无限的,这带来了诸多问题.文章针对计算资源有限MEC系统中的计算卸载,分析了最大化MEC总收益的卸载与资源分配联合优化问题.首先通过Stackelberg模型来描述MEC与用户之间的交互,使用差异化定价策略增加对卸载的约束,然后将卸载问题转化为二元背包问题,最后,通过改进模拟退火算法分配计算资源,并迭代得到最优方案.仿真结果表明,所提方案可以最大程度提高用户卸载数量,并有效地提高了MEC系统的收益.
Mobile edge computing(MEC)can effectively serve task computing by sinking the computing center to the edge of the network.However,the computing resources of MEC are not unlimited,which brings many problems.This paper analyses a joint optimization problem between unloading and resource allocation to maximize the total revenue of MEC for computational resources finite MEC systems.Firstly,the interaction between MEC and users is described through the Stackelberg model,the differential pricing strategy is used to increase the constraints on unloading,and then the unloading problem is transformed into a binary backpack problem.Finally,the computing resources are allocated by improving the simulated annealing algorithm,and the optimal scheme is obtained by iteration.Simulation results show that the proposed scheme can maximize the number of user unloading and effectively improve the benefits of MEC systems.
作者
鲜永菊
宋青芸
郭陈榕
刘闯
XIAN Yong-ju;SONG Qing-yun;GUO Chen-rong;LIU Chuang(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)
出处
《小型微型计算机系统》
CSCD
北大核心
2022年第8期1782-1787,共6页
Journal of Chinese Computer Systems
基金
国家自然科学基金项目(61602073)资助.
关键词
计算资源有限
移动边缘计算
卸载策略
资源分配
limited computing resources
mobile edge computing
unloading strategy
resource allocation
