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Apache Storm's default task scheduling mechanism uses Round-Robin (Polling) to distribute tasks to each node evenly. The default scheduling cannot obtain the overall running state of the cluster, resulting in unreasonable resource allocation between nodes. Aiming at this problem, the advantages of ant colony algorithm on NP-hard problem combined with the topology characteristics of Storm itself are proposed. The optimization scheme of improved ant colony algorithm in Storm task scheduling is proposed. The optimal values of heuristic factors α and β were found by a large number of experiments, and the optimal number of iterations of the improved ant colony algorithm in Storm task scheduling was measured. The Sigmoid function was introduced to improve the volatilization factor ρ, so that it can be used with the program. Run adaptive adjustment. Thereby reducing the load of each node CPU, and improving load balancing between nodes, speeding up task scheduling efficiency. The experimental results show that the improved ant colony algorithm and Storm's default polling scheduling algorithm reduce the average CPU load by 26%, while the CPU standard deviation is reduced by 3.5%. The algorithm efficiency is higher than Storm's default polling scheduling algorithm22.6%.