Dynamic task scheduling algorithm of parallel computing for FCD big data

FCD (floating car data) technique is new way of collecting real-time traffic flow from large-scale urban networks. It is necessary to implement rapid processing of FCD big data for the dynamic guidance and control of urban traffic. A dynamic task scheduling algorithm is proposed for parallel computation of FCD. To address the uncertainty and dynamics of FCD package processing, FCD packages are partitioned dynamically. The load balance among computing nodes can be achieved using the dynamic task allocation strategy. The algorithm is developed on LoongSon big data integrated machine platform and evaluated using field FCD. The experimental results indicate that the proposed algorithm has significantly higher parallel processing performances compared to the polling scheduling algorithm and Min-Min scheduling algorithm.