Various IoT devices constantly generate data in terms of time, which may form a large-scale of sequential data. Entropy calculation of a big data input will lead to unacceptable time, even not able to obtain the output. In this paper, we propose a distributed method for accelerating the entropy calculation process. Utilize a high performance host sever to deploy a distributed computing platform by server virtualization technique. Run independent R environment for the entropy calculation in multiple computing nodes and adopt Java multi-thread technique in one control node. From the experiment results and the analysis, we can conclude that the proposed distributed scheme is efficient and feasible for dealing with large-scale sequential data.