MNSRQ: Mobile node social relationship quantification algorithm for data transmission in Internet of things

Abstract

The rapid development of the Internet of things has led to the explosive development of data in various fields. Traditional routing protocols cannot effectively handle the reception and transmission of data. This makes it difficult to exchange and transmit information in the Internet of things. Therefore, the choice of data transmission methods is particularly important. In order to solve this problem, this paper proposes a data transmission mechanism based on social relationships, namely, the mobile node social relationship quantification (MNSRQ) algorithm, which analyses the social relationship characteristics of mobile nodes in the Internet of things, extracts decision‐making features to study the dynamics of social relationship, then combines information entropy and fuzzy clustering theory to quantify the social relationship, and then selects the relay node with strong social relationship for data transmission. Theoretical analysis and experimental results show that the performance of the MNSRQ algorithm is better than previous studies. Compared with epidemic algorithm, ICMT algorithm, spray and wait algorithm, and EIMST algorithm, the MNSRQ algorithm can reduce end‐to‐end transmission delay and routing overhead while maintaining the life of the network, effectively reduce energy consumption during transmission, and maintain a high data transmission success rate, with a transmission success rate of 0.7–0.9.