花瓣网络上最快的分布式共识
Fastest Distributed Consensus on Petal Networks
摘要：
为寻找最快分布式共识（FDC）问题提供解析解是传感器网络领域的挑战性问题之一。在这项工作中，我们提出了最快的分布式共识平均算法的问题的分析解决方案，通过分层和半定规划，两种特殊类型的花瓣网络，即对称和完全核心对称（CCS）花瓣网络。该方法基于最快分布式共识平均问题的凸性，通过对松弛条件下的特征多项式进行归纳比较，找到最优权值。还介绍了某些类型的叶子以及它们的最佳权重，如果单独考虑这些叶子，则这些权重无法通过本工作中使用的方法实现。
英文摘要：
Providing an analytical solution for the problem of finding Fastest Distributed Consensus (FDC) is one of the challenging problems in the field of sensor networks. Here in this work we present analytical solution for the problem of fastest distributed consensus averaging algorithm by means of stratification and semi-definite programming, for two particular types of Petal networks, namely symmetric and Complete Cored Symmetric (CCS) Petal networks. Our method in this paper is based on convexity of fastest distributed consensus averaging problem, and inductive comparing of the characteristic polynomials initiated by slackness conditions in order to find the optimal weights. Also certain types of leaves are introduced along with their optimal weights which are not achievable by the method used in this work if these leaves are considered individually.
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