Wireless sensor network congestion control technology based on PID controller
A wireless sensor and control technology, applied in the field of PID queue congestion management, to achieve the effect of reducing packet loss rate, improving WSN environment, and saving network resources
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[0070] see Figure 1 to Figure 10 Shown, be the embodiment of the present invention, comprise the control schematic diagram of the PNPID algorithm of the embodiment of the present invention, flow chart, PI, PID, the queue length of the PNPID algorithm of the embodiment of the present invention, throughput, packet loss rate experimental comparison chart .
[0071] The working process and principle of this embodiment are:
[0072] The present invention will be described in detail below in conjunction with the accompanying drawings: Although compared with other WSN network congestion, PI and PID are an effective congestion control mechanism, but they still have the following shortcomings.
[0073] 1. In the past, WSN congestion control strategies mostly focused on congestion detection and congestion processing. These strategies only deal with congestion after it occurs, which has a certain lag and consumes limited energy of WSN; while PI, PID controller and active queue The con...
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, 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.
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