## 1 Introduction
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Company** & **Google** & **Microsoft** & **Amazon** & **Alibaba Cloud** \\
**Attributes** & & & & \\ \hline Data resource service & Google Public Data Explorer & Windows Azure & Public datasets & Data Cube \\ Big data storage service & Google Cloud services & Azure & S3 & DataX \\ MapReduce & Google Application (App) Engine & Hadoop on Azure & Elastic MapReduce (EMR) & Cloud Ladder \\ Big data analysis service & BigQuery & Hadoop on Azure & EMR & Garuda \\ NoSQL database & App engine datastore & Table storage & DynamoDB & Open Table Service (OTS) \\ Relational database & Cloud Structured Query Language & SQL Azure & MySQL and Oracle & Myfox and MySQL \\  & (SQL) & & \\ Streaming service & Search Application Programming & StreamInsight & None & Galaxy \\  & Interface (API) & Hadoop + Mabout & Hadoop + Mabout & Open data processing services (ODPS) \\ Machine learning service & Prediction API & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: List of typical cloud-based big data tools. Cloud computing technology is closely related to the development of CLICP technology. [PERSON] and [PERSON] [32] analyzed the security of cloud computing in a railway environment and proposed a cloud computing security reference framework. [PERSON] et al. [33] gave an overview of intelligent railway transportation systems--including cloud computing technology--and analyzed the future of such systems. [PERSON] et al. [34] applied support vector machines to the prediction of train delays. The majority of publications on cross-border logistics and information platform cover issues related to intermodal transportation; existing research has not considered the significance of the CR Express to cross-border logistics and the importance of cloud technology to its information platforms. Ultimately, research on cross-border logistics has focused less on the modes of public, rail, and land transport; traditional logistics is still based on road transportation's high cost and limited transportation capacity, which is based on the trunk railway transportation form of CR Express. Trends indicate the necessity of understanding a future in which receiving and delivery services with door-to-door transportation are completed by road and railway transportation. Moreover, cloud computing technology is developing quickly, with governments and Internet companies actively promoting the upgrading of related technologies. However, cross-border logistics has not yet been introduced into cloud computing and big data technology. A small number of studies have excavated the massive operation data from the business work accumulated over the years. Research on the transformation of cross-border logistics service models from traditional to information and digitization must be further carried out using cloud computing technology. In this paper, we focus on CLICP construction and design. The remainder of the paper is structured as follows. The following section contains a technology analysis of the proposed CLICP, and its construction scheme is designed in the fourth section. Our final section outlines the conclusion from the research in this paper.