Research And Implementation Of Energy Saving Transmission Technology Of Energy-limited Wireless Sensor Network Based-on Software Definition

Software-defined wireless sensor network is a kind of new network architecture which rises rapidly in the internet-of-things era.The network has the characteristics of strong expansibility,low design cost and simple layout.However,with more and more practical application scenarios appearing in which all nodes are energy-limited,this network architecture also exposes problems such as unbalanced energy consumption of nodes,the restriction of network lifetime due to the key node and so on.Therefore,it has become a matter of the utmost urgency to design new energy-saving routing algorithms in energy-limited wireless sensor network based-on software definition.In this paper,cluster software-defined wireless sensor network is designed to achieve the integration of data packages by the peculiarity of clustered architecture.Nowadays with the rapid development of artificial intelligence technology,thanks to its distinguishing feature about the achievement of any complex nonlinear mapping,back propagation neural networks is deeply integrated with amounts of fields,which brings qualitative leap for various fields of technology.Hence we use BP neural network model to design a cluster-node selection algorithm based-on node energy level,which takes the remaining energy and other parameters of the node as the network input,and BP neural network as the scoring system to select the most suitable cluster head node for the current network.The cluster node selected can complete the function of data aggregation and transmission,so as to reduce the energy consumption caused by the data transmission of the node.Simulation results show that the algorithm mentioned above can effectively slow down the energy consumption rate of each node in the network.In addition,aiming at the problem of restriction about the key node in the network,this paper also designs controller election algorithm based-on adaptive handoff.The algorithm is also based on BP neural network,for the network to select the appropriate node as the backup controller.On one hand,when the energy of the current controller is too low to be the controller,the controller functions are switched to the standby controller to realize the energy balance of the network.On the other hand,when the current controller fails and leaves the network,the standby controller can automatically upgrade to the active controller to ensure the normal operation of the network.As the simulation results shown,the algorithm improves the lifetime of the network greatly.