The Advantage of Computation Offloading in Multi-Access Edge Computing

Raghubir Singh, S. Armour, Aftab Khan, M. Sooriyabandara, G. Oikonomou
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引用次数: 8

Abstract

Computation offloading plays a critical role in reducing task completion time for mobile devices. The advantages of computation offloading to cloud resources in Mobile Cloud Computing have been widely considered. In this paper, we have investigated different scenarios for offloading to less distant Multi-Access Edge Computing (MEC) servers for multiple users with a range of mobile devices and computational tasks. We present detailed simulation data for how offloading can be beneficial in a MEC network with varying quantitative mobile user demand, heterogeneity in mobile device on-board and MEC processor speeds, computational task complexity, communication speeds, link access delays and mobile device user numbers. Unlike previous work where simulations considered only limited communication speeds for offloading, we have extended the range of link speeds and included two types of communication delay. We find that more computationally complex applications are offloaded preferentially (especially with the higher server:mobile device processor speed ratios) while low link speeds and any delays caused by network delays or excessive user numbers degrade any advantages in reduced task completion times offered by offloading. Additionally, significant savings in energy usage by mobile devices are guaranteed except at very low link speeds.
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多访问边缘计算中计算卸载的优势
计算卸载在减少移动设备的任务完成时间方面起着至关重要的作用。在移动云计算中,计算卸载到云资源的优势已经得到了广泛的关注。在本文中,我们研究了为具有一系列移动设备和计算任务的多个用户卸载到距离较近的多访问边缘计算(MEC)服务器的不同场景。我们提供了详细的模拟数据,说明在具有不同数量移动用户需求、移动设备板载和MEC处理器速度的异质性、计算任务复杂性、通信速度、链路访问延迟和移动设备用户数量的MEC网络中,卸载是如何有益的。不像以前的工作,模拟只考虑有限的通信速度卸载,我们扩大了链路速度的范围,并包括两种类型的通信延迟。我们发现,更多计算复杂的应用程序优先被卸载(特别是在服务器:移动设备处理器速度比更高的情况下),而低链路速度和由网络延迟或过多用户数量引起的任何延迟会降低卸载在减少任务完成时间方面提供的任何优势。此外,除了非常低的连接速度外,移动设备的能源使用可以保证显著节省。
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