标题： RC-Gossip：具有速率变化的Gossip的分组网络中的信息新鲜度 显示英文标题

标题： RC-Gossip: Information Freshness in Clustered Networks with Rate-Changing Gossip

摘要： 在一个聚类播送网络中，源节点随时间更新其信息，终端节点通过簇头组织成簇，持续跟踪该信息。 节点的目标是尽可能保持最新，即拥有与源节点相同的信息，我们通过长期平均二进制最新度指标来评估这一点。 我们引入了一种智能的信息传播机制，我们称之为速率变化播送（RC-Gossip）。 其主要思想是将播送定向到最需要它的节点，因此播送的速率会根据网络中当前最新节点的数量而变化。 虽然随机混合系统（SHS）分析一直是研究播送网络最新度的标准方法，但我们提出了一种等效的方法，使用基于更新-奖励的分析来研究最新度。 利用这种方法，我们证明与传统播送技术相比，RC-gossip在不同聚类网络中显著提高了节点的最新度，尤其是在最优簇大小的情况下。 显示英文摘要

摘要： A clustered gossip network is considered in which a source updates its information over time, and end-nodes, organized in clusters through clusterheads, are keeping track of it. The goal for the nodes is to remain as fresh as possible, i.e., have the same information as the source, which we assess by the long-term average binary freshness metric. We introduce a smart mechanism of information dissemination which we coin rate-changing gossip (RC-Gossip). Its main idea is that gossiping is directed towards nodes that need it the most, and hence the rate of gossiping changes based on the number of fresh nodes in the network at a given time. While Stochastic Hybrid System (SHS) analysis has been the norm in studying freshness of gossip networks, we present an equivalent way to analyze freshness using a renewal-reward-based approach. Using that, we show that RC-gossip significantly increases freshness of nodes in different clustered networks, with optimal cluster sizes, compared to traditional gossiping techniques.