Data transmission method in mobile social network based on swarm intelligence

Abstract

The invention discloses a data transmission method in a mobile social network based on swarm intelligence. The method comprises the following steps of A, using a modeling method to analyze a data distribution problem in the mobile social network to summarize a general model of the mobile social network; B, using an ant colony optimization-based mobile social network (ACOMSNet) algorithm by using high efficiency of an ant colony optimization algorithm for processing an optimization problem on the basis of the summarized general model of the mobile social network; C, aiming at the defect that the ACOMSNet algorithm is prone to trap in local optimum, fusing a particle swarm optimization algorithm with the ACOMSNet algorithm to acquire the improved ACOMSNet algorithm; and D, aiming at a selfish node in the network, using an incentive mechanism algorithm applicable to the mobile social network based on a reputation value of the node. According to the method of the invention, routing is optimized by using a thought of ant colony optimization and particle swarm optimization in a swarm intelligence theory, and thus the mobile social network can have a higher data transmission success rate and a lower time delay.

Description

Technical field [0001] The invention relates to the field of mobile social network data transmission, in particular to a data transmission method in a mobile social network based on swarm intelligence. Background technique [0002] With the rapid development of the Internet industry, the widespread popularity of smart mobile terminals, and the advent of the 4G mobile Internet era, the natural combination of social network services and mobile terminals has been promoted, and mobile social networks have emerged. Data research shows that in the world, although the current population growth has been relatively slow, the development speed of the Internet industry has been accelerating. Currently, more than half of the world’s population owns a mobile phone, and one third of them have social network accounts. In China, according to WeAreSocial's "2015 Global Mobile & Social Report Essence Interpretation", the current Chinese population is about 1.367 billion, with about 642 million I...

AI Technical Summary

Problems solved by technology

First of all, nodes in mobile social networks are usually some mobile terminal devices, and their service capabilities are limited by bandwidth, memory, power, computing power, etc.; secondly, nodes in mobile social networks are often accompanied by people’s social characteristics. It brings great complexity to the design of the data distribution mechanism; finally, considering that the nodes in the mobile social network usually have human selfishness, how to take measures to reduce the damage caused by selfish nodes to network performance is a difficult problem

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