Research On Resource Allocation Of Optical WSNs Based On Node Position And Energy Consumption

In recent years,with the wide application of wireless sensor networks(WSNs),its problems in terms of tight spectrum resources,severe electromagnetic interference,and low power efficiency have become increasingly prominent.Free space optical(FSO)communication has the advantages of abundant spectrum resources,strong anti-interference and fast transmission rate.This makes optical WSNs that combine FSO communication with WSNs attract much attention.Unlike radio frequency communication(RF)communication,the availability and reliability of FSO communication are susceptible to changes in the atmospheric environment.Therefore,in order to achieve efficient and energy-efficient cooperative communication in optical WSNs,this paper studies and analyzes the network model,node position optimization,dynamic distance calculation and resource allocation in optical WSNs,then proposes an adaptive distributed resource allocation strategy based on node position and energy consumption.The main work contents are as follows :(1)Because FSO communication is line-of-sight communication,it is easily blocked by obstacles when it is used in ground communication,which affects network performance.Therefore,this paper constructs a layered structure of hybrid optical WSNs model,which consists of multiple clusters.The upper-layer network consists of optical nodes as cluster heads(CHs),and uses FSO links for inter-cluster communication.The lower-layer network consists of ordinary nodes that are cluster members(CMs),and uses RF links for intra-cluster communication.(2)In the transmission process,the optical signal will cause power loss due to beam divergence and atmospheric conditions,and even cause link interruption,which greatly reduces the network connectivity.Therefore,this paper considers the transmission power and analyzes the connectivity conditions of the upper layer network.Furthermore,under the condition of ensuring the connectivity of the upper layer network,with the minimum network energy consumption as the fitness function,the position of CHs in the upper layer network is optimizedbased on the particle swarm optimization algorithm(PSO),so that the upper layer network can obtain Low energy connectivity.(3)Considering the dynamic changes of nodes in the network,this paper adopts a dynamic Euclidean Distance(ED)calculation method for the active nodes in the cluster.Taking the real-time signal as the object of consideration,the auto correlation function(ACF)is analyzed,and the dynamic calculation of ED is realized by updating the ACF error between the signals in real time.This helps CHs to dynamically allocate resources based on real-time distance changes,thereby achieving efficient and energy-saving cooperative communication.(4)This paper models optical WSNs based on multi-agent theory and improves on traditional multi-agent methods,thus proposing an adaptive layered resource allocation strategy.Considering the importance of CHs in the network,this paper adds an adaptive inter-cluster task migration mechanism to the upper-layer network resource allocation.CHs can timely migrate tasks to neighbor nodes with high FSO link reliability and large resources based on real-time assessment of its own resource amount,thereby reducing the failure rate of CHs.In the resource allocation of the lower layer network,the method of combining dynamic alliance and PSO algorithm is adopted,which mainly improves the formation and optimization goal of dynamic alliance.In the initial alliance,node distance,energy load and task running time constitute the objective function to perform optimal task assignment based on PSO algorithm.Simulation results show that compared with traditional methods,the proposed method can effectively reduce CHs failure rate and network energy consumption,and improve the task processing speed.It adds intelligence and energy saving to the network in the process of resource allocation,thereby achieving better collaboration performance.