| 基于蚁群算法的移动边缘服务器收益优化策略 |
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| 引用本文： | 黄冬艳,付中卫,李浪. 基于蚁群算法的移动边缘服务器收益优化策略[J]. 计算机应用与软件, 2022, 0(2): 95-99+214 |
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| 作者姓名： | 黄冬艳 付中卫 李浪 |
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| 作者单位： | 桂林电子科技大学广西无线宽带通信与信号处理重点实验室 |
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| 基金项目： | 广西科技基地和人才专项(桂科AD19110042);广西壮族自治区无线宽带通信与信号处理重点实验室主任基金项目(GXKL06160111)。 |
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| 摘 要： | 移动边缘计算(Mobile Edge Computing,MEC)是5G的关键技术。由于MEC服务器的计算资源有限,如何对其计算资源分配以提高收益至关重要。为此,提出一种边缘服务器收益优化策略。将MEC服务器收益最大化问题建模为以服务器端任务执行次序为优化变量的最优化问题。在用户对时延和金钱偏好程度不同及子任务具有顺序执行关联性的情况下,提出基于蚁群算法的任务最优执行次序求解算法。仿真结果表明,同等条件下采用该算法获得的收益比SearchAdjust算法提高了33.6%。
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| 关 键 词： | 移动边缘计算 最优化 蚁群算法 SearchAdjust算法 |
REVENUE OPTIMIZATION STRATEGY OF MOBILE EDGE SERVER BASED ON ANT COLONY ALGORITHM |
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| Huang Dongyan,Fu Zhongwei,Li Lang. REVENUE OPTIMIZATION STRATEGY OF MOBILE EDGE SERVER BASED ON ANT COLONY ALGORITHM[J]. Computer Applications and Software, 2022, 0(2): 95-99+214 |
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| Authors: | Huang Dongyan Fu Zhongwei Li Lang |
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| Affiliation: | (Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing,Guilin University of Electronic Technology,Guilin 541004,Guangxi,China) |
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| Abstract: | Mobile edge computing(MEC)is a key technology for 5G.Due to the limited computing resources of MEC server,how to allocate its computing resources to improve revenue is crucial.To this end,an edge server revenue optimization strategy is proposed.The MEC server revenue maximization problem was modeled as an optimization problem with the server-side task execution order as an optimization variable.In the case where users have different degrees of delay and money preferences and sub-tasks have a sequential execution correlation,a task optimal execution order solution algorithm based on ant colony algorithm was proposed.The simulation results show that under the same conditions,the revenue obtained by the proposed algorithm is 33.6%higher than the SearchAdjust algorithm. |
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| Keywords: | Mobile edge computing Optimization Ant colony algorithm SearchAdjust algorithm |
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