Research On Routing Strategy And Its Application In Named Data Networking

Named Data Network is a new type of network architecture under the InformationCentric Networking paradigm that adopts a content-centric communication mode,improving traditional end-to-end communication.The academic community has studied the NDN routing mechanism based on the fundamental principle of NDN content forwarding,and designed the existing NDN routing strategies.In scenarios with unconstrained network scale and dynamics,improving the content retrieval success rate is a key issue in NDN data routing protocol design,which still requires further research.Furthermore,due to NDN’s better data transmission efficiency and stronger content caching ability,using NDN’s characteristics to improve data transmission and distribution in vehicular ad hoc networks has also been a recent research hotspot.This paper mainly focuses on the routing forwarding strategy in the field of Named Data Networks.It analyzes the problems faced by the existing NDN routing forwarding and the scalability of the mechanism,summarizes three stages and four directions of routing strategies,and proposes routing strategies applicable to the second and third stages.To address the low routing hit rate of traditional routing strategies,a multi-factor comprehensive ant colony optimization routing algorithm is proposed,which adopts an optional next hop method and congestion control to ensure network transmission stability.The experimental results show that the proposed method can effectively reduce the risk of network congestion.Regarding the routing problem in vehicular ad hoc networks,this paper introduces NDN into it and proposes a vehicular Named Data Network routing strategy based on the Sarsa machine learning algorithm.The simulation results show that the proposed method has significant advantages in packet hit rate and end-to-end delay performance.The specific work is as follows:1.Addressing the current research progress of NDN routing and forwarding,the problems faced by route forwarding are broadly classified as the expansion of routing table size,high complexity of route finding and blindness of route forwarding methods.The scalability of NDN routing mechanisms,large-scale forwarding under the core features of NDN,and the updating of PIT tables in NDN nodes are also analysed.The applicability of each of the existing routing strategies is analysed and they are broadly classified into four categories and three phases,with the first phase being content prefix-oriented routing and cache optimizationoriented routing,the second phase being quality of service oriented routing,and the third phase being practical application-oriented routing.Finally,the future directions are summarized and in the subsequent part of the thesis routing strategies for the second and third phases are proposed respectively.2.Aiming at the accuracy problem of ant colony routing algorithm in the forwarding process,the existing research has not given a specific solution,and proposed an ant colony routing optimization algorithm with comprehensive consideration of multiple factors.Referring to the traditional ant colony ecological behavior and the elite strategy in genetic algorithm,and taking into account the pheromone concentration on the path between nodes,the path length between neighbor nodes,and the content similarity between the request node and the forwarding node,an optional next hop method is used to forward the interest ants to a high probability node to determine the best interest ant routing path;The method of content aggregation and node conversion control is used for congestion control to ensure the stability of network transmission.The experimental results show that under the condition of limited network space resources,when the number of routing interest packets increases to a certain threshold,compared with the ant colony algorithm,the average routing life rate is improved,the average routing delay is reduced,and risk of network congestion can be reduced more effectively.3.A named data network routing strategy based on Sarsa machine learning algorithm is proposed.Methods The overall idea is divided into two parts:in road selection,fuzzy logic method and depth first search algorithm are used to obtain and utilize the global road information,that is,RSU collects the global road traffic information,summarizes and analyzes it,and then forwards it to the ground requesting vehicle.When selecting the vehicle node,the vehicle maintains a fixed size Q value table,which has a specially designed reward function and forwards the route.By searching the filtered Q value table,the best node is requested to guide the global route.Simulation results show that the proposed method has great advantages in packet hit rate and end-to-end delay.