This work studies video transcoding and multicast in an edge computing network (ECN), where routers are furnished with computing resources. For example, the recent IPv6-SRv6 paradigm enables programmable networking that works in concert with such hardware innovations, provisioning application-defined route selection and realizing compute&forward functionalities. A prominent class of user applications in ECN is video streaming. Edge routers may replicate and transcode video streams while delivering them toward end users for customized services, up to node processing and link transmission capacities. We design an auction-based online optimization framework DOP, which comprises of three components: video access management, dynamic price function design, as well as transcoding multicast tree (TMT) optimization. We formulate the online social welfare maximization problem, and design an efficient primal-dual framework that simultaneously makes video transcoding, multicast routing and resource pricing decisions. Through rigorous theoretical analysis, we prove DOP guarantees truthfulness and achieves a good competition ratio. Extensive simulations further verify that social welfare increases by about 12.9%, in comparison to benchmark algorithms.

中文翻译：

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边缘计算网络中转码组播的动态优化和定价


这项工作研究了边缘计算网络（ECN）中的视频转码和组播，其中路由器配备了计算资源。例如，最近的 IPv6-SRv6 范式支持与此类硬件创新协同工作的可编程网络，提供应用程序定义的路由选择并实现计算和转发功能。 ECN 中一类突出的用户应用程序是视频流。边缘路由器可以复制和转码视频流，同时将其传送给最终用户以提供定制服务，直至节点处理和链路传输能力。我们设计了一个基于拍卖的在线优化框架DOP，它由三个部分组成：视频访问管理、动态价格函数设计以及转码多播树（TMT）优化。我们提出了在线社会福利最大化问题，并设计了一个高效的原对偶框架，该框架同时进行视频转码、组播路由和资源定价决策。通过严格的理论分析，我们证明DOP保证了真实性并达到了良好的竞争比。大量模拟进一步验证，与基准算法相比，社会福利增加了约 12.9%。