Task distribution algorithm based on community in mobile crowd sensing

Abstract

A community-based task distribution algorithm was proposed to solve the problem of the validity of mobile crowd sensing (MCS) task distribution.By calculating the minimum spanning tree (MST),the connection parameter (CP) and the community convergence degree (CI) between the mobile nodes,the behavior patterns of the users were abstracted and identified to rationally divide the nodes into different communities.Then,the eigenvalue matching degree of the community behavior patterns with the sensing task was calculated.According to the matching degree,the distribution of the corresponding tasks was completed by the central node of the community.The simulation results show that the proposed method can effectively improve the accuracy of the task distribution and the task completion rate,and save the time cost of the task completion.

Keywords

• mobile crowd sensing;community;behavior pattern;task distribution;matching degree