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Self-Adapting Routing Overlay Network for Frequently Changing Application Traffic in Content-Based Publish/Subscribe System

机译:自适应路由覆盖网络,用于在基于内容的发布/订阅系统中频繁更改应用程序流量

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In the large-scale distributed simulation area, the topology of the overlay network cannot always rapidly adapt to frequently changing application traffic to reduce the overall traffic cost. In this paper, we propose a self-adapting routing strategy for frequently changing application traffic in content-based publish/subscribe system. The strategy firstly trains the traffic information and then uses this training information to predict the application traffic in the future. Finally, the strategy reconfigures the topology of the overlay network based on this predicting information to reduce the overall traffic cost. A predicting path is also introduced in this paper to reduce the reconfiguration numbers in the process of the reconfigurations. Compared to other strategies, the experimental results show that the strategy proposed in this paper could reduce the overall traffic cost of the publish/subscribe system in less reconfigurations.
机译:在大规模分布式仿真区域中,覆盖网络的拓扑无法始终快速适应频繁变化的应用程序流量,从而降低了总体流量成本。在本文中,我们提出了一种自适应路由策略,用于在基于内容的发布/订阅系统中频繁更改应用程序流量。该策略首先训练流量信息,然后使用该训练信息来预测将来的应用流量。最后,该策略根据此预测信息重新配置覆盖网络的拓扑,以降低总体流量成本。本文还介绍了一种预测路径,以减少重新配置过程中的重新配置次数。与其他策略相比,实验结果表明,本文提出的策略可以减少重新配置,从而降低发布/订阅系统的总体流量成本。

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