The Hybrid network model was introduced in [Augustine et al., SODA '20] for laying down a theoretical foundation for networks which combine two possible modes of communication: One mode allows high-bandwidth communication with neighboring nodes, and the other allows low-bandwidth communication over few long-range connections at a time. This fundamentally abstracts networks such as hybrid data centers, and class-based software-defined networks. Our technical contribution is a \emph{density-aware} approach that allows us to simulate a set of \emph{oracles} for an overlay skeleton graph over a Hybrid network. As applications of our oracle simulations, with additional machinery that we provide, we derive fast algorithms for fundamental distance-related tasks. One of our core contributions is an algorithm in the Hybrid model for computing \emph{exact} weighted shortest paths from $\tilde O(n^{1/3})$ sources which completes in $\tilde O(n^{1/3})$ rounds w.h.p. This improves, in both the runtime and the number of sources, upon the algorithm of [Kuhn and Schneider, PODC '20], which computes shortest paths from a single source in $\tilde O(n^{2/5})$ rounds w.h.p. We additionally show a 2-approximation for weighted diameter and a $(1+\epsilon)$-approximation for unweighted diameter, both in $\tilde O(n^{1/3})$ rounds w.h.p., which is comparable to the $\tilde \Omega(n^{1/3})$ lower bound of [Kuhn and Schneider, PODC '20] for a $(2-\epsilon)$-approximation for weighted diameter and an exact unweighted diameter. We also provide fast distance \emph{approximations} from multiple sources and fast approximations for eccentricities.
翻译:混合网络模型被引入 [ Augustine 和 al., SODA'20] 用于为混合网络中结合两种可能的通信模式的网络奠定一个理论基础: 一种模式允许与邻近节点进行高频/ 频度的通信, 而另一种模式允许一次在少数远程连接中进行低频/ 频度的通信。 这种基本简易网络, 如混合数据中心, 和基于类的软件定义网络。 我们的技术贡献是一个 emph{ 度- 觉知 方法, 使我们能够模拟一套 直径( emph{ ) 直径, 用于混合网络中的多端骨架图 。 作为我们提供的附加机器, 我们为基本的远程任务制定快速算法。 一种核心贡献是混合模型中的算法, 从 $tilde O( n=1/3) 直径( ==xxx) 来完成 直径( =xxxx) 直径( n=xxxxxxx) 。 这改进了运行时间和运行中的源数, 从O=xx。