Research On Robustness Strategy For Internet Of Things With Adaptive Population Evolution

The Internet of Things(IoT)has been widely used to monitor,collect and process surrounding environmental information.And,they are often deployed in inaccessible and complex environments such as plateaus,canyons,deserts and deep seas.The failure of sensor nodes caused by harsh and complex environments and hidden and frequent network attacks will seriously affect network stability and communication quality.Therefore,it is important to optimize the network connections and construct a topology with high robustness in IoT.In this dissertation,the probability density function of 2D Gaussian distribution is used to simulate 3D terrain with multiple peaks.In addition,this dissertation considers the communication range of sensor nodes in the IoT,the upper limit of energy,and the occlusion of the node signal by the 3D terrain,so as to design a model that generates the initial scale-free IoT topology.Although the scale-free IoT topology is highly resistant to random attacks,it is very vulnerable to malicious attacks.In order to solve the above problem,this dissertation proposes an adaptive robustness evolution algorithm(AERA)with self-competition,which is composed of population initialization,crossover operation,mutation operation,local search and self-competition mechanism.At the same time,in order to achieve an effective assessment of population diversity,this dissertation also designs a population diversity measurement method PD,and combines this method to achieve adaptive adjustment of the mutation rate.AREA enhances the initial scale-free IoT topology's ability to resist malicious attacks by swapping edges based on the location and connection information of the nodes,and this method can ensure that the optimized topology has the same scale-free properties as the initial topology.The simulation results demonstrate that AREA is more effective in improving the robustness of scale-free IoT networks than several existing methods.In addition,the scale-free IoT topology optimized by AREA can still maintain its scale-free characteristics.Meanwhile,AREA is still applicable to network robust optimization in 3D terrain.Therefore,in the future construction of the IoT,the method of this dissertation can be employed to perform topology modeling and topology robust optimization on the deployed device nodes,and then employ the optimized topology structure to guide the construction of the actual IoT connections.