论文标题
联合计算机通信控制用于在线数据密集型服务交付
Joint Compute-Caching-Communication Control for Online Data-Intensive Service Delivery
论文作者
论文摘要
新兴的元应用应用程序旨在提供高度交互式和沉浸式的体验,这些体验无缝地融合了物理现实和数字虚拟性,它正在加速使用具有前所未有的存储,计算和通信要求的分布式计算平台的需求。为此,下一代网络(例如5G及以后)以及分布式云技术(例如,雾和移动边缘计算)的综合演变已成为一种有希望的范式,以解决元应用应用程序的交互和资源密集型性质。在本文中,我们专注于在下一代分布式云网络中进行连接,缓存和通信(3C)资源的控制策略的设计,以有效地交付需要实时汇总,处理和分布多个实时媒体流和预存储的数字资产的元应用程序。我们通过定向的无环图描述了元应用程序,能够建模实时流处理和内容分布管道的组合。我们设计了第一个吞吐量 - 最佳控制策略,该策略围绕(i)围绕(i)路由路径和处理实时数据流的处理位置,以及(ii)相关数据对象的缓存选择和分配路径。然后,我们将提出的解决方案扩展到包括最大通讯数据库放置策略和两个有效的替换策略。此外,我们还表征了所有研究场景的网络稳定区域。数值结果表明,与缺乏完整3C集成控制的最新算法相比,通过新型的多上线流量控制和3C资源编排机制获得的出色性能。
Emerging Metaverse applications, designed to deliver highly interactive and immersive experiences that seamlessly blend physical reality and digital virtuality, are accelerating the need for distributed compute platforms with unprecedented storage, computation, and communication requirements. To this end, the integrated evolution of next-generation networks (e.g., 5G and beyond) and distributed cloud technologies (e.g., fog and mobile edge computing), have emerged as a promising paradigm to address the interaction- and resource-intensive nature of Metaverse applications. In this paper, we focus on the design of control policies for the joint orchestration of compute, caching, and communication (3C) resources in next-generation distributed cloud networks for the efficient delivery of Metaverse applications that require the real-time aggregation, processing, and distribution of multiple live media streams and pre-stored digital assets. We describe Metaverse applications via directed acyclic graphs able to model the combination of real-time stream-processing and content distribution pipelines. We design the first throughput-optimal control policy that coordinates joint decisions around (i) routing paths and processing locations for live data streams, together with (ii) cache selection and distribution paths for associated data objects. We then extend the proposed solution to include a max-throughput database placement policy and two efficient replacement policies. In addition, we characterize the network stability regions for all studied scenarios. Numerical results demonstrate the superior performance obtained via the novel multi-pipeline flow control and 3C resource orchestration mechanisms of the proposed policy, compared with state-of-the-art algorithms that lack full 3C integrated control.