Abstract: In order to establish a permanent and stable task distribution link in the perceptual service process, firstly, an intimacy quantification method based on social attributes(IQSA) was proposed; secondly, a community detection algorighm based on information entropy similarity（CDIES）was proposed by combining the information entropy theory with social relationship; finally, IQSA algorithm was compared with two popular models by experiments, and the accuracy and validity of CDIES algorithm was assessed according to the result of community devision, modularity and time cost. The experimental results show that, compared with the content-based friend recommendation and relationship-based two typical recommendation algorithms, the IQSA algorithm has best comprehensive performance in accuracy, recall, and f1-score. And the modularity and time cost of the result of community devision of CDIES algorithm outperforms that of GN algorithm and FN algorithm. 

Key words: crowdsensing, social relationship, task distribution, information entropy, community devision, modularity, time cost