Applying multiple sink nodes in a large‐scale wireless sensor networks (WSN) can increase the scalability and lifetime of the network. The current sink selection mechanisms assume an unlimited amount of buffer and bandwidth for the sink nodes. This can be problematic in real‐world applications, especially when many cluster heads select a specific sink node and send their data to the sink at the same time. In this situation, the sink node may not have enough buffer to receive and process data; consequently, some packets are dropped. To mitigate these occasions, a fuzzy‐based controller with reduced rules is proposed for sink selection by considering the capacity of the sink nodes. The capacity of the sink nodes is estimated using the long short‐term memory (LSTM) technique. Then another fuzzy‐based controller with reduced rules is designed to select the cluster head. The fuzzy rules are reduced by employing R‐implications method. Reducing the number of fuzzy rules decreases the complexity of the fuzzy controllers. The results show the efficiency of the proposed sink selection and clustering techniques in terms of consumed energy, remaining energy, first node dead (FND), half nodes dead (HND), last node dead (LND), packet loss, and delay.

中文翻译：

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无线传感器网络中基于模糊控制器的汇选择和聚类

在大型无线传感器网络（WSN）中应用多个接收器节点可以提高网络的可伸缩性和寿命。当前的接收器选择机制假定接收器节点的缓冲区和带宽数量不受限制。这在实际应用中可能会出现问题，尤其是当许多群集头选择特定的接收器节点并将其数据同时发送到接收器时。在这种情况下，接收器节点可能没有足够的缓冲区来接收和处理数据。因此，某些数据包被丢弃。为了缓解这些情况，通过考虑宿节点的容量，提出了一种具有减少规则的基于模糊控制器，用于宿选择。接收器节点的容量是使用长短期记忆（LSTM）技术估算的。然后，设计了另一个具有简化规则的基于模糊的控制器来选择簇头。模糊规则通过采用R-蕴涵方法来减少。减少模糊规则的数量会降低模糊控制器的复杂度。结果表明，在消耗的能量，剩余能量，第一个节点失效（FND），半个节点失效（HND），最后一个节点失效（LND），数据包丢失和延迟方面，建议的宿选择和聚类技术的效率。