Joint Optimization of Storage and Transmission via Coding Traffic Flows for Content Distribution
Joint Optimization of Storage and Transmission via Coding Traffic Flows for Content Distribution
复制标题
DOI：
10.23919/wiopt58741.2023.10349849
复制
发表时间：
2023-08
期刊：
影响因子：
--
通讯作者：
Derya Malak;Yuanyuan Li;Stratis Ioannidis;Edmund M. Yeh;Muriel Médard
中科院分区：
文献类型：
--
作者：
Derya Malak;Yuanyuan Li;Stratis Ioannidis;Edmund M. Yeh;Muriel Médard
我们为以信息为中心的网络提供基于流的编码缓存框架。我们根据需求和网络拓扑共同优化传输速率、交叉编码和缓存内容分配。我们的模型考虑了存储和传输成本、需求不对称和任意多跳拓扑，并依赖于成对编码流创建的传输的基于有序流的解码调度。通过对多种拓扑的广泛实验，我们观察到我们的编码缓存方案比竞争对手降低了几个数量级的传输成本。
We provide a flow-based coded caching framework for information centric networks. We jointly optimize delivery rates, cross coding, and cache contents allocation as a function of demand and the network's topology. Our model accounts for stor-age and transmission costs, demand asymmetry, and arbitrary multi-hop topologies, and relies on an ordered flow-based de-coding schedule for the transmissions created by pairwise coded flows. Through extensive experiments over multiple topologies, we observe that our coded caching scheme reduces transmission costs over competitors by several orders of magnitude.