The Smart Grid (SG) provides the bi-directional flow of data to overcome problems like shortage of electricity, electricity billing, managing fault, home automation so on. For the transfer of data, the integration of Cognitive Radio (CR) in sensor networks makes efficient communication possible in real-time monitoring. SG uses different technologies like WiFi, cellular network, ZigBee, optical cables depending upon the area of application. For effective communication, CR is used to allocate the unutilized spectrum from the Primary User to the Secondary User by sensing. This paper proposes a technique called Fuzzy Long Sort Term Memory based Crow Search Optimization Algorithm (FLSTM–CSOA) to allocate the best available spectrum with minimum delay. By comparing our proposed method with the existing technique, the simulation result shows that the FLSTM–CSOA has better performance in terms of BER (10⁻¹), throughput (200 kbps), and latency (10 ms).

中文翻译：

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认知驱动负载管理决策支持的基于无线传感器网络的智能电网

智能电网（SG）提供双向数据流，以解决电力短缺，电费，故障管理，家庭自动化等问题。为了进行数据传输，传感器网络中集成了认知无线电（CR），可以在实时监控中进行有效的通信。SG根据应用领域使用不​​同的技术，例如WiFi，蜂窝网络，ZigBee，光缆。为了有效通信，CR用于通过感应将未使用的频谱从主要用户分配给次要用户。本文提出了一种基于模糊长排序记忆的乌鸦搜索优化算法（FLSTM–CSOA），以最小的延迟分配最佳的可用频谱。通过将我们提出的方法与现有技术进行比较，^-1），吞吐量（200 kbps）和延迟（10 ms）。