Application Research On Improved Ant Colony Algorithm In The Routing Selection Of RINA

At present,the Internet has grown and benefited everyone,but with the development of science and technology,the Internet currently faces many problems,such as routing table,mobile and multi-homing.In order to solve these problems,researchers have painstakingly researched and achieved a lot of results,including some architectures different from Transmission Control Protocol/Internet Protocol(TCP/IP),and The Recursive Inter Network Architecture(RINA)is one of them.RINA now supports routing algorithms based on both distance vector and link state.But the algorithm to find the optimal path is relatively simple.Therefore,a new algorithm to find the optimal path is proposed and implemented in RINA,which is necessary.First of all,this thesis studies RINA and its communication principle.RINA returns to the most basic concept of communication: inter-process communication.The architecture has one basic principle and two main design principles.The basic principle is inter-process communication and only inter-process communication.One of the two main design principles is recursion,the other is separation of mechanisms and policy.In RINA,the network is not a collection of different functional layers,but a repetition of a single layer of communication between distributed processes in different scopes.This repeated single layer is called Distributed Inter-Process Communication Facility(DIF).A node joins the DIF through registration,then by generating flow,the error and flow control protocol and the relay and multiplexing protocol,the node in the DIF implements the inter-process communication,executing the logout procedure after communication ends,releasing resources.Secondly,the classical ant colony algorithm is analyzed and studied,and an improved algorithm P-ACS is proposed based on Ant System(AS)algorithm and Particle Swarm Optimization(PSO).Through analysis and experiment,it is found that although the ant algorithm has many advantages,there are still some problems,such as: falling into local optimal solution,search stagnation and slow initial convergence.The important reason for the above problems is that the pheromone update can not accurately reflect the actual situation of the path.Aiming at this problem,the algorithm optimizes the pheromone update strategy from four aspects: pheromone concentration range setting,initial pheromone setting,pheromone update strategy and state transition strategy.Finally,the RINA network simulation environment is deployed locally,and the improved algorithm P-ACS is deployed to RINASim.Verify the correctness,feasibility and effectiveness of the P-ACS algorithm in the RINA network.