Dear editor,rnSpatial crowdsourcing(SC)services(e.g.,Uber,DiDi,and Meituan)have become popular with smart-phone growth.However,the online matching problems in real-time spatial data are a key issue in SC[1-4].Unlike the current one-sided online matching study in real-time spatial data[5],which focuses on minimizing the overall cost of the matching,we focus on minimizing the bottleneck cost,i.e.,minimizing the maximum distance cost of the matching.The reason why we consider the bottleneck optimization goal is explained in Appendix A.The real-time minimum bottleneck matching(RMBM)problem in SC is defined as follows.