Lin Lin, Shi You, Chen Jinfu, Ali Sher
School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China.
Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace, Jiangsu University, Zhenjiang 212013, China.
Sensors (Basel). 2020 Mar 27;20(7):1862. doi: 10.3390/s20071862.
Wireless Sensor Networks (WSNs) consist of multiple sensor nodes, each of which has the ability to collect, receive and send data. However, irregular data sources can lead to severe network congestion. To solve this problem, the Proportional Integral Derivative (PID) controller is introduced into the congestion control mechanism to control the queue length of messages in nodes. By running the PID algorithm on cluster head nodes, the effective collection of sensor data is realized. In addition, a fuzzy control algorithm is proposed to solve the problems of slow parameter optimization, limited adaptive ability and poor optimization precision of traditional PID controller. However, the parameter selection of the fuzzy control algorithm relies too much on expert experience and has certain limitations. Therefore, this manuscript proposes the Cuckoo Fuzzy-PID Controller (CFPID), whose core idea is to apply the cuckoo search algorithm to optimize the fuzzy PID controller's quantization factor and PID parameter increment. Simulation results show that in comparison with the existing methods, the instantaneous queue length and real-time packet loss rate of CFPID are better.
无线传感器网络（WSNs）由多个传感器节点组成，每个节点都具备收集、接收和发送数据的能力。然而，不规则的数据源可能导致严重的网络拥塞。为了解决这个问题，将比例积分微分（PID）控制器引入到拥塞控制机制中，以控制节点中消息的队列长度。通过在簇头节点上运行PID算法，实现了传感器数据的有效收集。此外，还提出了一种模糊控制算法，以解决传统PID控制器参数优化速度慢、自适应能力有限和优化精度差的问题。然而，模糊控制算法的参数选择过于依赖专家经验，具有一定的局限性。因此，本文提出了布谷鸟模糊PID控制器（CFPID），其核心思想是应用布谷鸟搜索算法来优化模糊PID控制器的量化因子和PID参数增量。仿真结果表明，与现有方法相比，CFPID的瞬时队列长度和实时丢包率更好。
