边缘计算中有限资源下基于aco的任务卸载方法

Xueshuo Chen, Yuxing Mao, Hongyu Wang, Yihang Xu, Xiong Xiong, Danyang Li
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引用次数: 0

摘要

边缘计算的提出是为了解决随着物联网(IoT)设备及其产生的数据数量的增加而产生的数据处理问题。任务卸载问题在该领域受到广泛关注,并进行了大量的研究。然而,大多数研究考虑的是通过虚拟化技术在云服务器或边缘服务器上进行数据处理和任务卸载,而不是在资源受限的终端(rct)上进行处理和任务卸载,因为rct上有大量的数据集,甚至不能很好地支持Docker。为此,本文提出了一种随机对照试验的资源模型和一种新的物联网任务描述,有利于物联网资源的管理,并将物联网服务清晰地分组。该方法便于蚁群算法求解资源受限环境下的任务卸载问题。通过仿真分析,该方法可以在短时间内有效地解决该问题,保证了边缘计算系统的实时性和超轻量性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ACO-based Task Offloading Method with Limited Resource in Edge Computing
Edge computing is put forward to solve the problem of data processing with an increasing number of Internet of Things (IoT) devices and the data generated by them. Task offloading problem gets lots of attention in this field with a great deal of research. However, most research consider data processing and task offloading on cloud server or edge server with virtualization technology rather than resource-constrained terminals (RCTs) where large sets of data come from that cannot even support Docker well. For this reason, this paper proposes a kind of resource model of RCTs and a novel description of IoT tasks that are beneficial to management of IoT resource with which services of IoT are grouped clearly. Then that method makes it convenient for ACO performing to solve task offloading problem under resource-constrained environment. Through the analysis of simulation, this approach can deal with that problem within a short time effectively which ensures the real-time and ultra-lightweight of edge computing system.
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