Wireless sensor network congestion control technology based on PID controller

Abstract

The invention discloses a wireless sensor network congestion control method based on a PID controller by adopting a computer program. The method comprises the steps of: defining and initializing related parameters; embedding a PID queue management congestion algorithm obtained by combination of a PID control technology and an active queue management method into a wireless sensor network environment; setting fixed parameters (K, K and K<d>) of a PID controller by using a mono-neuron control technology; performing online optimization of the initial parameters (K<P0>, K<I0> and K<d0>) of a neuron PID controller and the neuron learning rates (eta<1>, eta<2> and eta<3>) by using an improved particle swarm optimization; and, after three parameters of the PID controller adaptive to the dynamic wireless sensor network environment are obtained, calculating the abandon probability (P), and abandoning a data packet, wherein the learning factor for optimization by adopting the particle swarm optimization is as follows: C<1>=0.95+0.1*rand, C<2>=C<1>; and the value of a weighting coefficient (w(k)) is adjusted by using a guide Hebb learning algorithm. Thereby, the parameters of the PID queue congestion algorithm are adjusted online; therefore, the parameters are suitable for characteristics of the wireless sensor network; and thus, the purpose of relieving the wireless sensor network congestion is achieved.

Description

technical field [0001] The invention relates to a PID queue congestion management method related to wireless sensor network congestion control, more specifically, a PID-based wireless sensor network node queue congestion management method. Background technique [0002] There is a problem of wireless sensor network congestion in wireless sensor networks. The congestion of wireless sensor networks can be divided into two types: one type is node-level congestion, that is, the packet flow that the node needs to send exceeds the sending capacity of the node, resulting in buffer overflow. The loss of data packets and the increase of network queuing delay; another type is congestion at the wireless link level. The wireless channel is a shared channel. At the same time, only one adjacent node can use the wireless channel. When multiple adjacent nodes At the same time, when competing to use the wireless channel, access conflicts will occur, causing link-level congestion, increasing t...

AI Technical Summary

Problems solved by technology

The algorithm not only dynamically adjusts the fixed parameters of the PID algorithm through the neuron control technology, but also uses the improved particle swarm algorithm to optimize the parameters online, which overcomes the fact that the PID congestion control method cannot well adapt to the WSN dynamic environment.

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