Research On Network Communication Link Monitoring And Dynamic Routing Optimization Method

At present,communication technology,big data,AI,Io T,edge computing and other cutting-edge technologies have extensive applications and lightful prospects,especially in the two fields of accelerating government construction and intelligent medical system.Since the development of these technologies cannot be separated from optical communication as the basic technical support,maintaining the robustness of optical communication network in the information communication system is the top priority of the tasks and challenges we are facing at present.Compared with the traditional cable communication technology,optical communication network has been a mature,convenient laying,cost saving,flexible networking,stronger manageability,high reliability network communicat ion technology and has the advantages of traditional communication technology can not be compared.Nowadays,optical network communication technology is widely used in the backbone of communication network all over the world.If the optical network fails and the workers fail to find and fix it in time,this behavior will cause significant losses to the industry.If the optical network fails and the workers fail to find and fix it in time,this behavior will cause significant losses to the industry.However,the traditional optical network fault detection measures will physical resources and waste numerous manpower.Consequently,the optical cable automatic detection system is used to detect the state of each optical fiber thread in real time and obtain the relevant information when the optical fiber occurs abnormal or fault in this paper.In order to detect all fiber link states in optical network,this paper proposes a method to solve the joint optimization of test node selection and fiber thread connection in this system.The problem is modeled as an integer linear programming problem with two sets of decision variables.The first class of decision variables are composed of the numbers of parallel fiber threads throughout each potential testing route,the other class of decision variables are imposed just to denote whether a node is decided as a location to place testing equipment.The objective of the joint optimization is to minimize the number of nodes where fiber test equipment based on the optical time domain reflectometer are planned to locate.The objective function is just the sum of the second class of decision variables.Two types of linear constraints were needed.The first type of constraints describe s the mutual relation between the two classes of variables,and the other type of constraints are formed to depict the impact of the number of fiber threads mounted within each fiber link on the first class of decision variables.An example is given to exhibit the advantage of joint optimization over heuristic method.In the optical network,the joint optimization method has been used to detect the fiber link state of the entire optical network.Next,under the background of the network management system dynamically updating the network topology,this pa per is to dynamically plan a data transmission path with the lowest time delay and network load balance.This paper presents a hybrid algorithm for optimal path planning.In the initial stage,the algorithm mainly uses the particle swarm optimization based on the adaptive inertia weight.In the process of particle updating,the algorithm abandons the conventional particle updating strategy,instead,it learns from the historically optimal particle with poor performance or from the particle with better perfo rmance.In order to prevent the algorithm from falling into local optimum prematurely,the adaptive inertia weighting factor can enlarge the searching range of particles.When the population is trapped in the local optimum,the genetic algorithm using the adaptive crossover operator and the adaptive mutation operator makes the population jump out of the local optimum.Compared with the traditional genetic algorithm and particle swarm optimization algorithm can be found to have a superior and more robust performance.In the context of dynamic ground network topology,the optimal route for packet transmission will use the hybrid algorithm described above to plan the optimal route for transmission in real time.