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Lower Bound for Function Computation in Distributed Networks

机译:分布式网络中函数计算的下界

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Distributed computing network systems are modeled as graphs with which vertices represent compute elements and adjacency-edges capture their uni- or bi-directional communication. Distributed computation over a network system proceeds in a sequence of time-steps in which vertices update and/or exchange their values based on the underlying algorithm constrained by the time-(in)variant network topology. For finite convergence of distributed information dissemination and function computation in the model, we present a lower bound on the number of time-steps for vertices to receive (initial) vertex-values of all vertices regardless of underlying protocol or algorithmics in time-invariant networks via the notion of vertex-eccentricity.
机译:分布式计算网络系统被建模为图形,其顶点表示计算元素,而邻接边捕获其单向或双向通信。网络系统上的分布式计算以一系列时间步骤进行,其中顶点基于时变网络拓扑约束的基础算法来更新和/或交换其值。为了使模型中的分布式信息分发和函数计算达到有限收敛,我们提出了一个时间步数下限,该时间步数用于接收所有顶点的(初始)顶点值,而不管时不变网络中的底层协议或算法如何。通过顶点偏心的概念。

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