MEC-TO-CTI

异构边缘网络复杂计算任务卸载数据集。 移动终端与物联网设备的广泛部署，使计算需求由传统后台批处理逐步转向强交互、强时效、高不确定性的在线智能业务，典型应用包括移动多媒体理解、车联网协同感知、工业视觉质检与超密集蜂窝网络等。这类任务普遍面临端侧算力与电量受限、无线链路波动明显以及业务侧对时延和可靠性要求严格等约束。在此背景下，任务卸载成为缓解终端资源瓶颈、提升服务效率的重要手段。通过将任务从移动设备迁移至网络边缘执行，任务卸载能够减轻终端计算负担，降低远距离传输带来的时延开销，并为5G、6G环境下不断涌现的新型智能应用提供更加高效的服务支撑。 本数据集模拟复杂场景下，真实边缘设备进行任务卸载时执行计算的过程。Heterogeneous Edge Network Complex Computing Task Offloading Dataset. The widespread deployment of mobile terminals and Internet of Things (IoT) devices has gradually shifted computing demands from traditional background batch processing to highly interactive, latency-sensitive, and highly uncertain online intelligent services. Typical applications include mobile multimedia understanding, cooperative perception in vehicular networks, industrial visual inspection, ultra-dense cellular networks, and other similar scenarios. These tasks generally face multiple constraints: limited computing power and battery capacity on the terminal side, significant fluctuations in wireless links, and strict requirements for latency and reliability from the service side. Against this backdrop, task offloading has emerged as a critical approach to alleviating terminal resource bottlenecks and improving service efficiency. By migrating tasks from mobile devices to the network edge for execution, task offloading can reduce the computational burden on terminals, lower the latency overhead caused by long-distance transmission, and provide more efficient service support for emerging novel intelligent applications in 5G and 6G environments. This dataset simulates the computing execution process when real edge devices perform task offloading in complex scenarios.

搜集汇总

背景与挑战

背景概述

MEC-TO-CTI是一个异构边缘网络复杂计算任务卸载数据集，模拟真实边缘设备在复杂场景下执行任务卸载的计算过程。该数据集旨在支持移动终端与物联网设备在强交互、强时效业务中的计算需求，通过任务卸载缓解终端资源瓶颈并提升服务效率。