| 引用本文： |
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彭璧莹,李陶深,陈燕.基于遗传-粒子群优化算法带有缓存机制的卸载策略[J].广西科学,2022,29(5):901-907. [点击复制]
- PENG Biying,LI Taoshen,CHEN Yan.Offloading Strategy with Caching Mechanism Based on Genetic-Particle Swarm Optimization Algorithm[J].Guangxi Sciences,2022,29(5):901-907. [点击复制]
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| 摘要: |
| 为了满足移动边缘计算(Mobie Edge Computing,MEC)场景中时延敏感型应用的需求，提出一种基于遗传-粒子群优化算法(Genetic-Particle Swarm Optimization Algorithm,GA-PSO)和缓存机制的卸载策略。该策略将遗传算法和粒子群优化(Particle Swarm Optimization,PSO)算法融合起来，以便求取边缘计算卸载中的最优卸载比例和缓存决策；将已完成且重复请求的任务及相关数据在边缘云上进行缓存，用以最小化任务的卸载时延。仿真实验结果表明，该策略可以有效降低移动边缘计算的时延。 |
| 关键词: 移动边缘计算 遗传-粒子群优化算法 时延 缓存机制 计算卸载策略 |
| DOI：10.13656/j.cnki.gxkx.20221116.010 |
| 投稿时间：2021-11-29修订日期：2022-01-11 |
| 基金项目:广西科技计划项目(桂科AD20297125)和国家自然科学基金项目(61762010) 资助。 |
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| Offloading Strategy with Caching Mechanism Based on Genetic-Particle Swarm Optimization Algorithm |
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PENG Biying1, LI Taoshen1,2, CHEN Yan1
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| (1.School of Computer, Electronics and Information, Guangxi University, Nanning, Guangxi, 530004, China;2.Guangxi Key Laboratory of International Join for China-ASEAN Comprehensive Transportation, Nanning University, Nanning, Guangxi, 530200, China) |
| Abstract: |
| In order to meet the needs of delay-sensitive applications in Mobile Edge Computing (MEC) scenarios,an offloading strategy based on Genetic-Particle Swarm Optimization Algorithm (GA-PSO) and caching mechanism is proposed.The strategy combines genetic algorithm and Particle Swarm Optimization (PSO) algorithm to obtain the optimal offloading ratio and caching decision in edge computing offloading.The completed and repeatedly requested tasks and related data are cached on the edge cloud to minimize the offloading delay of the task.The simulation experiment results show that this strategy can effectively reduce the delay of mobile edge computing. |
| Key words: Mobile Edge Computing Genetic-Particle Swarm Optimization Algorithm delay caching mechanism calculation offloading strategy |
