车联网边缘计算的多目标均衡任务卸载方法研究
Journal of Chinese Computer Systems（2022）
Abstract
随着边缘计算技术的逐渐成熟,各种对时延有苛刻需求的应用相继产生.虽然云中心能够为用户提供强大的计算能力,但是由于距离遥远无法提供实时的服务,边缘计算是很好的解决办法.移动边缘计算通过将任务卸载到边缘设备上,使用户能够灵活的获取计算资源等服务.本文首先对边缘计算环境下车辆通信模式选择进行了研究和分析,车载应用产生的服务需求可以卸载到配备边缘服务器的路侧单元进行处理,也可以卸载到邻近的车辆进行计算,使路侧单元服务效率最大化.本文根据K-means聚类算法对车辆通信模式进行合理选择,然后针对基于边缘计算的车联网架构通过非支配排序遗传算法在负载均衡、时间消耗和能量消耗3个目标函数之间取得平衡,最后得到了最优的卸载决策,仿真结果表明,本文所提出的算法大大提升了车联网架构的服务质量.
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