Community Detecting Oriented Directed and Weighted Network in Mobile Crowd Sensing

In mobile crowd sensing, data collection, delivery, and service interaction are all based on users with smart terminal. But in real life, there is no such pre-existing trust relationship among users. Users only forward data or service requests to familiar nodes and ignores the requests or data from unfamiliar users. One of the main problems of mobile crowd sensing is to detect the community structure and achieve trust interaction between users. In the existing community detecting methods of mobile crowd sensing, the weights and direction of the edges were often not considered. This paper introduces a community detection algorithm oriented on directed and weighted network. Reasonable division of the network can be realized by calculating the node activity, relationship strength, relationship density and community coupling degree. Experimental results show that our method can effectively detect and identify the communities in social relationship network, and have a better performance in contrast to the existing algorithm.