A universal routing algorithm based on intuitionistic fuzzy multi-attribute decision-making in opportunistic social networks

Abstract

With the vigorous development of big data and the 5G era, in the process of communication, the number of information that needs to be forwarded is increasing. The traditional end-to-end communication mode has long been unable to meet the communication needs of modern people. Therefore, it is particularly important to improve the success rate of information forwarding under limited network resources. One method to improve the success rate of information forwarding in opportunistic social networks is to select appropriate relay nodes so as to reduce the number of hops and save network resources. However, the existing routing algorithms only consider how to select a more suitable relay node, but do not exclude untrusted nodes before choosing a suitable relay node. To select a more suitable relay node under the premise of saving network resources, a routing algorithm based on intuitionistic fuzzy decision-making model is proposed. By analyzing the real social scene, the algorithm innovatively proposes two universal measurement indexes of node attributes and quantifies the support degree and opposition degree of node social attributes to help node forward by constructing intuitionistic fuzzy decision-making matrix. The relay nodes are determined more accurately by using the multi-attribute decision-making method. Simulation results show that, in the best case, the forwarding success rate of IFMD algorithm is 0.93, and the average end-to-end delay, network load, and energy consumption are the lowest compared with Epidemic algorithm, Spray and Wait algorithm, NSFRE algorithm, and FCNS algorithm.