【Author】
Aloqaily, Moayad; Bouachir, Ouns; Al Ridhawi, Ismaeel
【Source】2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)
【Abstract】Advanced services leveraged for future smart cities have played a significant role in the advancement of 5G networks towards the 6G vision. Interactive immersive applications are an example of those enabled services. Such applications allow for the interaction between multiple users in a 3D environment created by virtual presentations of real objects and participants using various technologies such as Virtual Reality (VR), Augmented Reality (AR), Extended Reality (XR), Digital Twin (DT) and holography. These applications require advanced computing models which allow for the processing of massive gathered amounts of data. Motions, gestures and object modification should be captured, added to the virtual environment, and shared with all the participants. Relying only on the cloud to process this data can cause significant delays. Therefore, a hybrid cloud/edge architecturewith an intelligent resource orchestration mechanism, that is able to allocate the available capacities efficiently is necessary. In this paper, a blockchain and federated learning-enabled predicted edge-resource allocation (FLP-RA) algorithm is introduced to manage the allocation of computing resources in B5G networks. It allows for smart edge nodes to train their local data and share it with other nodes to create a global estimation of future network loads. As such, nodes are able to make accurate decisions to distribute the available resources to provide the lowest computing delay.
【Keywords】Immersive Services; Autonomous Resource Management; Intelligent Edge; Blockchain; Federated Learning
【标题】交互式沉浸式服务的基于区块链和 FL 的网络资源管理
【摘要】面向未来智慧城市的先进服务在推动 5G 网络向 6G 愿景发展方面发挥了重要作用。交互式沉浸式应用程序是这些启用服务的一个示例。此类应用程序允许使用各种技术（例如虚拟现实 (VR)、增强现实 (AR)、扩展现实 (XR)、数字孪生 (DT)和全息。这些应用程序需要先进的计算模型，以便处理大量收集的数据。应捕获动作、手势和对象修改，将其添加到虚拟环境中，并与所有参与者共享。仅依靠云来处理这些数据可能会导致严重的延迟。因此，具有智能资源编排机制的混合云/边缘架构，能够有效地分配可用容量是必要的。在本文中，引入了一种区块链和联邦学习支持的预测边缘资源分配（FLP-RA）算法来管理 B5G 网络中计算资源的分配。它允许智能边缘节点训练其本地数据并与其他节点共享，以创建对未来网络负载的全局估计。因此，节点能够做出准确的决策来分配可用资源以提供最低的计算延迟。
【关键词】沉浸式服务；自主资源管理；智能边缘；区块链；联邦学习
评论