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A population theory inspired solution to the optimal bandwidth allocation for Smart Grid applications

机译:人口理论启发了智能电网应用最佳带宽分配的解决方案

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The establishment of a previously non-existent data class known as the Smart Grid will pose many difficulties on current and future communication infrastructure. It is imperative that the Smart Grid, as the reactionary and monitory arm of the Power Grid, be able to communicate effectively between grid controllers and individual UEs. Like most wireless sensor networks (WSN), the data sent by individual UEs has limited usefulness and precision. Collection of a large amount of data produces information that is useful to the system and which can be acted upon. However, this increases the communication traffic in an environment where communication traffic from other mobile users is already high. By ensuring effective communications between Distributed Generators and the Smart Grid, renewable resources that are subject to large fluctuations can be utilized more effectively and efficiently. This research proposes that a Proportional Fairness Algorithm, when combined with Lotka-Volterra Population Theory, will ensure fair bandwidth allocation for all User Equipment, whilst guaranteeing Smart Grid operating constraints such as minimal latency. Furthermore, the optimization of the bandwidth allocation maximizes Smart Grid Quality of Service, while also minimizing the decrease in Non-Smart Grid UE Quality of Experience.
机译:建立以前不存在的称为“智能电网”的数据类将给当前和未来的通信基础架构带来许多困难。至关重要的是,智能电网作为电网的反动和监测部门,必须能够在电网控制器和各个UE之间进行有效的通信。像大多数无线传感器网络(WSN)一样,各个UE发送的数据的实用性和准确性也受到限制。收集大量数据会产生对系统有用并可以采取措施的信息。但是,这在来自其他移动用户的通信流量已经很高的环境中增加了通信流量。通过确保分布式发电机与智能电网之间的有效通信,可以更有效地利用波动较大的可再生资源。这项研究提出,将比例公平算法与Lotka-Volterra人口理论相结合,将确保为所有用户设备分配公平的带宽,同时保证诸如最小等待时间之类的智能电网运行约束。此外,带宽分配的优化可最大化智能电网的服务质量,同时还可以最大程度地减少非智能电网UE体验质量的下降。

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