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

Robert Webster, K. Munasinghe, A. Jamalipour
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引用次数: 3

Abstract

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.
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一个人口理论启发了智能电网应用的最佳带宽分配解决方案
建立一个以前不存在的数据类,即智能电网,将给当前和未来的通信基础设施带来许多困难。智能电网作为电网的反动和监控臂,必须能够在电网控制器和各个终端之间进行有效的通信。与大多数无线传感器网络(WSN)一样,单个ue发送的数据的有用性和精度有限。大量数据的收集会产生对系统有用的信息,并且可以根据这些信息采取行动。然而,在其他移动用户的通信流量已经很高的环境中,这增加了通信流量。通过确保分布式发电机和智能电网之间的有效通信,可以更有效和高效地利用波动较大的可再生资源。本研究提出了一种比例公平算法,当与Lotka-Volterra人口理论相结合时,将确保所有用户设备的公平带宽分配,同时保证智能电网的运行约束,如最小延迟。此外,优化带宽分配可以最大限度地提高智能电网的服务质量,同时也可以最大限度地降低非智能电网UE的体验质量。
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