Research On Optimization Algorithm Of Service Node Configuration In Distributed Network

In the current era of information technology,the problem of network resource optimization has attracted much attention,and the research of network optimization algorithms has become a research hotspot in recent years.The network structure with distributed characteristics has high reliability and easy scalability,it has high application value in various fields.Therefore,the problem of resource optimization of distributed networks becomes particularly important.In distributed network resource optimization,the reasonable allocation of service node resources is the core of the entire distributed network.How to allocate service node resources to other nodes at low cost and high utilization rate is a problem that the distributed network service node configuration optimization algorithm should solve.Based on the knowledge of graph theory and the characteristics of distributed network communication,this paper constructs a distributed network service node configuration optimization model under various optimization objectives.When optimizing the network structure of the network graph,the shortest path calculation of the network is the primary problem.Due to the long execution time of the traditional Dijkstra algorithm,this paper gives the Dijkstra shortest path algorithm based on the two operations on the minimum plus algebraic field.The improved Dijkstra algorithm and traditional Dijkstra algorithm are compared and analyzed.Then improve the Dijkstra algorithm to solve the communication traffic between the network nodes,including the communication distance,cost,delay,etc.,and construct the network constraint discriminant matrix.Therefore,linear and nonlinear optimization models are established for the addition and deletion of service nodes,service node optimization of service nodes,and service node location reconfiguration optimization problems in a distributed network,and the corresponding algorithm process is given.For the linear programming model,the traditional simple algorithm is used to find the optimal solution.For the nonlinear programming model,the model is first linearized.For the non-linearized nonlinear programming model,an approximate search algorithm is used: genetic algorithm to find the optimal approximate solution of the model is obtained.Next,the three model algorithms are used to optimize the service node layout and demand point allocation of urban firefighting network,express network,and distributed communication network,respectively,which proves the effectiveness and applicability of the algorithm.Finally,this paper discusses the characteristics of the distributed network based on graph invariants,and uses the total cost of the network graph as the optimization goal to establish a nonlinear optimization model that optimizes the distributed network structure,solves the model through genetic algorithm,and optimizes the network of the distributed communication network.Service path.The four distributed network optimization algorithms proposed in this paper can effectively solve common distributed network service node configuration and resource optimization problems,they can be applied in a variety of application environments.After optimization,the distributed network meets the characteristics of global service and can effectively increase the utilization rate of network resources,which has certain guiding significance for the development of modern distributed network resource allocation optimization algorithms.