Cognitive Systems Research Centre, School of Engineering/Computer Science, London South Bank University, 103 Borough Road, London, SE1 0AA, UK.
Department of Mechatronics and Robotics School of Advanced Technology, Xi'an Jiaotong-Liverpool University (XJTLU), 111 Ren'ai Road, Suzhou, 215123, China.
Sci Rep. 2023 Jan 19;13(1):1063. doi: 10.1038/s41598-023-27674-5.
The developments on next generation IoT sensing devices, with the advances on their low power computational capabilities and high speed networking has led to the introduction of the edge computing paradigm. Within an edge cloud environment, services may generate and consume data locally, without involving cloud computing infrastructures. Aiming to tackle the low computational resources of the IoT nodes, Virtual-Function-Chain has been proposed as an intelligent distribution model for exploiting the maximum of the computational power at the edge, thus enabling the support of demanding services. An intelligent migration model with the capacity to support Virtual-Function-Chains is introduced in this work. According to this model, migration at the edge can support individual features of a Virtual-Function-Chain. First, auto-healing can be implemented with cold migrations, if a Virtual Function fails unexpectedly. Second, a Quality of Service monitoring model can trigger live migrations, aiming to avoid edge devices overload. The evaluation studies of the proposed model revealed that it has the capacity to increase the robustness of an edge-based service on low-powered IoT devices. Finally, comparison with similar frameworks, like Kubernetes, showed that the migration model can effectively react on edge network fluctuations.
下一代物联网传感设备的发展，伴随着其低功耗计算能力和高速网络的进步，催生了边缘计算范例。在边缘云环境中，服务可以在本地生成和消费数据，而不涉及云计算基础设施。为了解决物联网节点计算资源有限的问题，提出了虚拟功能链作为一种智能分配模型，以充分利用边缘的计算能力，从而支持高要求的服务。本文引入了一种具有支持虚拟功能链能力的智能迁移模型。根据该模型，边缘的迁移可以支持虚拟功能链的个别功能。首先，如果虚拟功能意外失败，可以通过冷迁移实现自动修复。其次，服务质量监控模型可以触发实时迁移，以避免边缘设备过载。对所提出模型的评估研究表明，它有能力提高低功耗物联网设备上基于边缘的服务的鲁棒性。最后，与 Kubernetes 等类似框架的比较表明，迁移模型可以有效地应对边缘网络波动。
