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首页> 外文期刊>Journal of network and systems management >Scalable Load Balancing and Flow Management in Dynamic Heterogeneous Wireless Networks
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Scalable Load Balancing and Flow Management in Dynamic Heterogeneous Wireless Networks

机译:动态异构无线网络中的可扩展负载平衡和流管理

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摘要

The number of connected devices has reached 18 billion in 2017 and this will nearly double by 2022, while also new wireless communication technologies become available. Since these modern devices support the use of multiple communication technologies, efforts have been made to enable simultaneous usage and handovers between the different technologies for these devices. However, existing solutions are missing the intelligence to decide on fine-grained (e.g. flow or packet level) optimizations that can drastically enhance the network's performance (e.g., throughput) and user experience. To this extent, we present a multi-technology flow-management load balancing approach for heterogeneous wireless networks that dynamically re-routes traffic through heterogeneous networks, in order to maximize the global throughput. This dynamic approach can be deployed on top of existing solutions and takes into account the specific characteristics of the different technologies, as well as station mobility. We both present a mathematical problem formulation and a heuristic that ensures practical scalability. We demonstrate the heuristic's ability to increase the network-wide throughput by more than 100% across a variety of scenarios and scalability up to 10,000 devices.
机译:2017年,已连接设备的数量已达到180亿,到2022年将增长近一倍,同时还会有新的无线通信技术可用。由于这些现代设备支持多种通信技术的使用,因此已经做出努力以使得这些设备的不同技术之间能够同时使用和切换。但是,现有的解决方案缺少决定细化(例如,流或分组级别)优化的智能,该优化可以极大地增强网络的性能(例如,吞吐量)和用户体验。在此程度上,我们提出了一种用于异构无线网络的多技术流管理负载平衡方法,该方法可以动态地通过异构网络重新路由流量,以使全局吞吐量最大化。可以将这种动态方法部署在现有解决方案之上,并考虑到不同技术的特定特征以及站点移动性。我们都提出了数学问题的提法和确保实际可伸缩性的启发式方法。我们证明了启发式技术能够在各种情况下将网络范围的吞吐量提高100%以上,并最多可扩展10,000个设备。

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