Research On Routing Algorithm Based On Fuzzy Decision Theory For Opportunistic Social Network

Opportunistic network is a network model facing the lack of continuous connection and extremely unstable network topology.The application of an opportunistic network in social scenes produces the opportunistic social network.Studying the design of routing algorithm in the opportunistic social network is an urgent problem to be solved,because designing reasonable routing algorithm can reduce the consumption of resources in the network and greatly increase the transmission efficiency.The research work of the routing algorithm based on the fuzzy decisionmaking theory and the intuitionistic fuzzy decision-making theory proposed in this dissertation is introduced as follows:1.According to the problems of socially aware routing algorithm,the problem definition of subsequent routing algorithm design is carried out.And defining the evaluation index used in the following chapters to judge the excellence of routing protocols.Then,it explains the feasibility of using two fuzzy decision-making theories from two aspects in this dissertation.On the one hand,the bibliometric analysis method is used to intuitively analyze the research trend of two fuzzy decision-making theories,as well as their research space in the opportunistic social network.On the other hand,starting with the specific literature,this dissertation analyzes the specific literature and application background of fuzzy decision-making theory in other types of networks.Finally,the reasons and practical significance of the selected four routing evaluation indexes are analyzed in detail.2.The multi-scene routing algorithm(MSFC,Multi-Scenario Routing Algorithm Based on Fuzzy Control Theory)based on the fuzzy decision-making theory divides the application scenarios of the algorithm into working time and non-working time according to real human activities.In the working time,MSFC algorithm uses the degree of intimacy and separation time as indicators.During the non-working time,MSFC algorithm uses interest sensitivity and age sensitivity as indicators.The algorithm uses a fuzzy decision-making system to calculate the forwarding preference of nodes.The fuzzy decision-making system includes the following three stages.In the fuzzification stage,the algorithm sets the Common Function for each node in the network,carries out fuzzification operation for both working time and non-working time,and uses the trichotomy to set the membership function.In the stage of fuzzy inference,the “IF A THEN B” rule is adopted to design fuzzy rules for the working time and the non-working time respectively.In the defuzzification stage,the maximum membership principle I is adopted to obtain the best next hop node set.3.The universal routing algorithm based on intuitionistic fuzzy decision-making model(Intuitionistic Fuzzy Decision-making,IFMD)firstly forms its own trust tendency in the preheating stage.Then,the population status and social similarity among nodes in the opportunistic social network are used to evaluate the social attributes of the nodes.The intuitionistic fuzzy decision-making matrix is constructed,and then the entropy weight method is used to determine the weight of each intuitionistic fuzzy set,and the comprehensive attribute value of the weighted average operator node is used.Finally,the similarity function is used to calculate the comprehensive score value of each node to obtain the final ranking of nodes,and the node with the highest comprehensive score value is selected as the next hop node for information forwarding.The best relay node is determined,by constructing the intuitionistic fuzzy matrix of node attributes and using the method of multi-attribute fuzzy decision-making.In the same experimental environment,the MSFC and IFMD algorithms proposed in this dissertation are compared with the other four routing algorithms,and the experimental results are measured by four indicators.Simulation results show that the routing algorithm proposed in this dissertation improves the forwarding rate and residual energy,and reduces the network overhead and average end-to-end delay.