# Development Policy of the International Trade Industry under the Background of Cloud Computing and Internet of Things

Authors: Liang Wu; Jianhua Zhou; Honglei Tang; Hanjie Xiao
Journal: Wireless Communications and Mobile Computing
 (2022)

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## Abstract

With the continuous development of Internet technology, new opportunities and challenges have emerged in international trade. If it does not seize new opportunities and take measures to meet challenges, it will cause the development of international trade to enter a state of stagnation, especially when the current domestic demand has not shown a strong recovery. The emergence of cloud computing and the Internet of Things (CCIoT) has provided new technologies and means for the development of international trade. In order to accurately analyze the development policy of the international trade industry and provide strong technical support for the development of the international trade industry under the Internet of Things environment, this paper studies the development policy of the international trade industry in the context of CCIoT. This paper borrows the method of cloud computing and collects relevant data provided by development policies through the perception Internet layer. It is transmitted through the network layer, processed through the high-performance computing cloud, and finally transformed into useful information for the international trade industry. The test results show that the use of cloud computing technology can analyze the existing development policies, promote the development of the international trade industry, and improve the trade efficiency by 3.84%. This reduces the impact of various factors on international trade, while providing strong and good services to users in international trade.


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## Body

## 1. Introduction

With the in-depth implementation of the “One Belt, One Road” policy, the current development of international trade is showing a positive trend. However, due to the influence of various factors, there are still many practical problems in the development of the international trade industry. In order to solve these problems, many experts have conducted research on the development policy of international trade, but few have considered the introduction of cloud computing IoT into the development policy of the international trade industry. This paper introduces CCIoT technology into the research of the international trade industry development policy, which plays an important role in solving practical problems. The international trade industry is an important support for the development of the national economy. The development of the international trade industry can provide a solid foundation for the development of the national economy. In order to improve the efficiency of international trade, many teams have conducted research on this. Hu et al. established an analysis framework based on a knowledge view for international trade enterprises. This is to better cultivate the innovation ability of the overall thinking process of domestic trade enterprises, and timely adjustment of the process can allow information capital to improve the performance of enterprises in the international trade industry [1]. In order to solve the problems faced by the international trade of traditional Chinese medicine, Cheng et al. used the Michael Porter diamond model to analyze the international competitiveness of the traditional Chinese medicine industry [2]. Chang examined the impact of disasters on international trade through the gravity equation model [3]. Rijesh examined the impact of international trade on Indian manufacturing productivity through the effects of economies of scale, reallocation, competition, and spillover channels [4]. Smith et al. proposed a multilevel network approach as an alternative framework for analyzing international organizations in the industrial sector of international trade [5]. Guliyev et al. discussed the current situation and related issues regarding the development of the oil refining industry worldwide [6]. Ishii studied firm dumping and antidumping duties by modeling international industries in which developed and developing country firms trade differentiated goods with each other under incomplete internalization of global pollution and pollution externalities [7]. Many teams have conducted research on the development of the international trade industry, but few teams have conducted research on the international trade industry in the context of cloud computing. For solving this problem, this paper introduces cloud computing into the international trade industry for research and analysis.The advantages of cloud computing make it used in various fields. To give full play to the advantages of cloud computing, many teams have conducted research on this. To address the inefficiency of retrieving localized data from remote clouds, Deng et al. leveraged cloud computing. They deployed localized computing facilities on the premise of users, prestored cloud data, and distributed it to mobile users with fast local connections [8]. Considering the competitive nature of multitenant environments in cloud computing, Wei et al. proposed a cloud resource allocation model using Hidden Markov Models in cloud computing environments based on incomplete information games [9]. Yi et al. chose to study how to improve the virtual machine sharing strategy from different perspectives to make it harder for intruders to attack the target [10]. Stergiou and Psannis have based on mobile cloud computing and IoT combined with big data technology to examine their common characteristics [11]. To alleviate the problem of long response times for workers that take a long time to process subtasks, Hirai et al. modeled the task scheduling server as a single-server queue [12]. Wang et al. proposed an efficient file-level attribute-based encryption scheme in cloud computing [13]. To improve scalability, availability, and durability, Barsoum and Hasan proposed a map-based provable multicopy dynamic data ownership (MB-PMDDP) scheme [14]. Xia et al. proposed a scheme that supports CBIR on encrypted images without leaking sensitive information to cloud servers. The feature vector is extracted to represent the corresponding image, and the prefiltering table is constructed by a local sensitive hash to improve the search efficiency. Security analysis and experiments prove the security and effectiveness of the proposed scheme [15]. Cloud computing studied by many teams does not involve the international trade industry. To promote the development of the international trade industry, this paper combines cloud computing and Internet of Things technology and introduces it into the study of its development policy.As the development of the international trade industry is closely related to people’s lives, people pay more and more attention to the development of the international trade industry. However, there are many problems in the development process of the international trade industry, which affect the development of the international trade industry. In order to solve various problems in the development of the international trade industry, this paper studies the development policies of the international trade industry under the background of CCIoT. The results showed that the introduction of CCIoT technology into the international trade industry can effectively reduce the impact of various factors on international trade, alleviate the blocking effect of various problems on its development, and improve trade efficiency. The Internet of Things refers to the realization of the ubiquitous connection between things and people and between things and people through various possible network accesses, and the realization of intelligent perception, identification, and management of objects and processes. The Internet of Things is an information carrier based on the Internet, traditional telecommunication networks, etc. It enables all common physical objects that can be independently addressed to form an interconnected network.


## 2. Cloud Computing IoT System

### 2.1. IoT Sensor Network System

The sensor network system [15] includes end nodes, router nodes, coordination nodes, and monitoring centers. The end nodes are located in the industrial exit zone. The location and number of end nodes and cameras can be placed according to actual needs. The system can handle all kinds of accidents in a timely manner and ensure the safe and rapid growth of the trade industry. The system block diagram is shown in Figure 1.Figure 1
The overall framework of the system.The end nodes send the collected data to other end nodes and process the data at the coordinating node. The wireless sensor monitoring system consists of end nodes, wireless router nodes, coordination nodes, data acquisition centers, and servers. The end nodes are placed high in the industrial area and can collect relevant data and transmit the data on the wireless network through wireless router nodes. First, they are sent to the coordinator and then to the scanner server via the serial port. Then the scanner server transmits the data to the monitoring center through the radio module, and finally, the monitoring center further completes the processing and storage of the data. As soon as the parameters deviate from normal conditions, an alarm is issued immediately. This allows employees and managers to take immediate action to prevent incidents of all kinds, thereby reducing the frequency of incidents. At the same time, the administrator can know from the network address from which site the data is sent. This helps employees and managers to take appropriate measures in a timely manner to improve work efficiency.


### 2.2. Cloud Computing Platform Management Technology

The cloud computing system is composed of a large number of servers and serves a large number of users at the same time. Therefore, the cloud computing system uses distributed storage to store data and redundant storage to ensure the reliability of data.A large number of cloud servers are distributed in different industrial export regions. In order to ensure that the entire cloud system [16] can provide services continuously, the international trade industry must make reasonable use of these export zone servers. Cloud computing platform management technology ensures that many servers work together. It also enables users to easily operate and control applications, and to detect and repair faults in a timely manner. The cloud computing platform management architecture is shown in Figure 2.Figure 2
Cloud system framework diagram.As shown in Figure2, the user layer provides relevant hardware configuration resources for the cloud computing service of the data layer by building a super-large-scale data center. At the same time, with the support of virtualization technology, it provides users with powerful computing power and other resources. It is especially convenient for users to publish applications. Users can intelligently select network components and set application publishing parameters without having to understand and manage the basic software and hardware facilities of cloud computing. As the middle layer of the three-layer core service, the data layer plays a role in linking the previous and the next. It not only undertakes the resource scheduling and management at the bottom of the system but also supplies the distributed programming framework to management software or applications. Due to the popularity of centralized data software applications and the increasing size of data, the data layer must have the ability to handle large data read and write operations that can adapt to the needs of modern applications.


### 2.3. GFS System

GFS is a data management system developed based on data center research and development and hosting network software applications [17]. The GFS system can meet the needs of the international trade industry to publish and operate network applications developed by enterprises. In addition, GFS is designed with the idea of storing files in blocks. Each block has a fixed size and is copied to multiple block servers simultaneously. It is located at the bottom of the core technology, which provides massive storage space for the international trade industry to facilitate large-scale trade in the international trade industry. The GFS architecture is shown in Figure 3.Figure 3
GFS system framework.As can be seen from Figure3, the user logs in to the GFS client through the application and can input the file name to be searched into the management node. The file meta management center converts the transmitted data into instruction information through the node and transmits it to the storage server. After that, the storage server will return the data queried in the file system and its own status information to the file meta management center. The file element management center then returns the file location information to the user. After the whole process, users can easily and quickly obtain the files they want.GFS is a scalable distributed file system for large, distributed applications that access large amounts of data. It runs on inexpensive commodity hardware and provides fault tolerance. It can provide services with high overall performance to a large number of users.By traditional standards, the files are very large. Files up to several gigabytes in length are not uncommon. Each file usually contains many application objects. When frequently dealing with rapidly growing datasets of terabytes in length containing tens of thousands of objects, it is difficult to manage tens of thousands of kilobytes of file blocks, even if the underlying file system supports it. Therefore, the operating parameters and block size in the design must be reconsidered. The management of large files must be efficient, and it must also support small files, but it does not need to be optimized.


### 2.4. Data Flow Diagram of the International Trade Industry

A data flow graph [18] uses a graphical tool to describe the flow of data input and output in an application. It uses a set of graphics or arrows to identify the input and output of the application, which can briefly and comprehensively describe the transmission process of information flow in the system. A data flow diagram treats the system as a complete entity. After the user inputs their own request information, the system processes the information and then outputs it to the user. The data flow diagram of the international trade industry is shown in Figure 4.Figure 4
Data flow diagram of the international trade industry.As can be seen from Figure4, the user can add, delete, modify, and check the six functional modules. The six functional modules also send commands to the database. After that, the database will return the data to the function module, and the function module will return the query result to the user. These six functional modules can meet the needs of users to a large extent.


### 2.5. Cloud Computing Task Scheduling Module

Cloud service management [19] usually consists of two processes: One is the source-based conference management direction, and the other is the user service query analysis center. The cloud computing components are shown in Figure 5.Figure 5
Cloud computing task scheduling module diagram.As can be seen from Figure5, after the user submits the service request, the user service analysis company collects and analyzes the access functions. It sorts the queue according to the user’s deadline, finds available resources, and calculates the execution of the corresponding work queue resources. Cloud source management has two main functions. One is to regularly check and update any source information to the cloud proxy server, and the other is to hold meetings of relevant sources to perform tasks. The pheromone is updated every time when the task is completed. The computing source corresponding to the component is periodically sent to the cloud source directory for storage.


## 2.1. IoT Sensor Network System

The sensor network system [15] includes end nodes, router nodes, coordination nodes, and monitoring centers. The end nodes are located in the industrial exit zone. The location and number of end nodes and cameras can be placed according to actual needs. The system can handle all kinds of accidents in a timely manner and ensure the safe and rapid growth of the trade industry. The system block diagram is shown in Figure 1.Figure 1
The overall framework of the system.The end nodes send the collected data to other end nodes and process the data at the coordinating node. The wireless sensor monitoring system consists of end nodes, wireless router nodes, coordination nodes, data acquisition centers, and servers. The end nodes are placed high in the industrial area and can collect relevant data and transmit the data on the wireless network through wireless router nodes. First, they are sent to the coordinator and then to the scanner server via the serial port. Then the scanner server transmits the data to the monitoring center through the radio module, and finally, the monitoring center further completes the processing and storage of the data. As soon as the parameters deviate from normal conditions, an alarm is issued immediately. This allows employees and managers to take immediate action to prevent incidents of all kinds, thereby reducing the frequency of incidents. At the same time, the administrator can know from the network address from which site the data is sent. This helps employees and managers to take appropriate measures in a timely manner to improve work efficiency.


## 2.2. Cloud Computing Platform Management Technology

The cloud computing system is composed of a large number of servers and serves a large number of users at the same time. Therefore, the cloud computing system uses distributed storage to store data and redundant storage to ensure the reliability of data.A large number of cloud servers are distributed in different industrial export regions. In order to ensure that the entire cloud system [16] can provide services continuously, the international trade industry must make reasonable use of these export zone servers. Cloud computing platform management technology ensures that many servers work together. It also enables users to easily operate and control applications, and to detect and repair faults in a timely manner. The cloud computing platform management architecture is shown in Figure 2.Figure 2
Cloud system framework diagram.As shown in Figure2, the user layer provides relevant hardware configuration resources for the cloud computing service of the data layer by building a super-large-scale data center. At the same time, with the support of virtualization technology, it provides users with powerful computing power and other resources. It is especially convenient for users to publish applications. Users can intelligently select network components and set application publishing parameters without having to understand and manage the basic software and hardware facilities of cloud computing. As the middle layer of the three-layer core service, the data layer plays a role in linking the previous and the next. It not only undertakes the resource scheduling and management at the bottom of the system but also supplies the distributed programming framework to management software or applications. Due to the popularity of centralized data software applications and the increasing size of data, the data layer must have the ability to handle large data read and write operations that can adapt to the needs of modern applications.


## 2.3. GFS System

GFS is a data management system developed based on data center research and development and hosting network software applications [17]. The GFS system can meet the needs of the international trade industry to publish and operate network applications developed by enterprises. In addition, GFS is designed with the idea of storing files in blocks. Each block has a fixed size and is copied to multiple block servers simultaneously. It is located at the bottom of the core technology, which provides massive storage space for the international trade industry to facilitate large-scale trade in the international trade industry. The GFS architecture is shown in Figure 3.Figure 3
GFS system framework.As can be seen from Figure3, the user logs in to the GFS client through the application and can input the file name to be searched into the management node. The file meta management center converts the transmitted data into instruction information through the node and transmits it to the storage server. After that, the storage server will return the data queried in the file system and its own status information to the file meta management center. The file element management center then returns the file location information to the user. After the whole process, users can easily and quickly obtain the files they want.GFS is a scalable distributed file system for large, distributed applications that access large amounts of data. It runs on inexpensive commodity hardware and provides fault tolerance. It can provide services with high overall performance to a large number of users.By traditional standards, the files are very large. Files up to several gigabytes in length are not uncommon. Each file usually contains many application objects. When frequently dealing with rapidly growing datasets of terabytes in length containing tens of thousands of objects, it is difficult to manage tens of thousands of kilobytes of file blocks, even if the underlying file system supports it. Therefore, the operating parameters and block size in the design must be reconsidered. The management of large files must be efficient, and it must also support small files, but it does not need to be optimized.


## 2.4. Data Flow Diagram of the International Trade Industry

A data flow graph [18] uses a graphical tool to describe the flow of data input and output in an application. It uses a set of graphics or arrows to identify the input and output of the application, which can briefly and comprehensively describe the transmission process of information flow in the system. A data flow diagram treats the system as a complete entity. After the user inputs their own request information, the system processes the information and then outputs it to the user. The data flow diagram of the international trade industry is shown in Figure 4.Figure 4
Data flow diagram of the international trade industry.As can be seen from Figure4, the user can add, delete, modify, and check the six functional modules. The six functional modules also send commands to the database. After that, the database will return the data to the function module, and the function module will return the query result to the user. These six functional modules can meet the needs of users to a large extent.


## 2.5. Cloud Computing Task Scheduling Module

Cloud service management [19] usually consists of two processes: One is the source-based conference management direction, and the other is the user service query analysis center. The cloud computing components are shown in Figure 5.Figure 5
Cloud computing task scheduling module diagram.As can be seen from Figure5, after the user submits the service request, the user service analysis company collects and analyzes the access functions. It sorts the queue according to the user’s deadline, finds available resources, and calculates the execution of the corresponding work queue resources. Cloud source management has two main functions. One is to regularly check and update any source information to the cloud proxy server, and the other is to hold meetings of relevant sources to perform tasks. The pheromone is updated every time when the task is completed. The computing source corresponding to the component is periodically sent to the cloud source directory for storage.


## 3. Algorithm Research of the International Trade Industry Based on Cloud Computing and Internet of Things

### 3.1. Network Throughput

The data in the network is composed of data packets, and the processing of each data packet by the firewall consumes resources. Throughput is the maximum rate a device can accept without frame loss. The test method is as follows: send a certain number of frames at a certain rate during the test, and calculate the frames transmitted by the device under test. If the number of frames sent is equal to the number of frames received, then the sending rate and retest are increased; if the frame is received, if there are fewer than sending frames, reduce the sending rate and retest until the final result is obtained. Throughput test results are expressed in bits per second or bytes per second.Network throughput [20] is an important metric used in many grid experiments. It represents the sending process from the beginning of sending data information to the destination node in the continuous process of a node or unit in the running mode. It is shown in the following:
(1)th=pkt_byte_sumxend_timex−timex−1×8/100.Among them,th is the throughput of the network, pkt_byte_sumx is the size of the data packet sent by process x, end_timex is the time when process j receives the data packet, and end_timej−1 is the time of the last received packet.


### 3.2. Membership

In the normal cloud model, the degree of membership obeys a normal distribution with expected entropyEn and farsightedness He as standard deviations, i.e., NEn,He2, which satisfies the degree of participation from x to C.
(2)μx=exp−x−Ex22En′2.x is the actual value, En′ obeys the En′~NEn,He2 distribution, and the value of He is smaller than the value of En. Therefore, when calculating μx, En can be used instead of En′.


### 3.3. Combinatorial Optimization Problem

Combinatorial optimization [21] is an optimization problem that studies different variables. The knapsack problem is an important part of the overall optimization, and it is also the most studied problem in the current overall optimization problem. The knapsack problem is how to choose within a limited total volume to maximize the total value of items. It can be formulated as a linear program as follows:
(3)KPmax∑m=1npmxms,t∑m=1nwmxm≤cxm∈0,1x=1..⋯,n.n is the number of items, and pi, mx, and m∈N=1,⋯,n are the value and weight of item m, respectively. c is a positive integer and is the capacity of the knapsack.


### 3.4. Wavelet Transform Function

Wavelet transform is a new transform analysis method. It inherits and develops the idea of localization of short-time Fourier transform, at the same time, overcomes the shortcomings of window size that does not change with frequency, can provide a “time-frequency” window that changes with frequency, and is an ideal tool for signal time-frequency analysis and processing.(4)Ea,bt=1aEt−ba.E is the wavelet function.


### 3.5. Wavelet Packet Function

(5)CE=2π∫−∞+∞Εφ2φdt<∞.


### 3.6. Continuous Wavelet Transform (CWT) Function

The CWT function is a transformation method proposed on the basis of the short-time Fourier transform. Its definition is shown in the following formula.(6)CWTa,b=∫−∞+∞ftΕa,btdt.


### 3.7. Continuous Wavelet Inverse Transform

The continuous inverse particle transform can reconstruct the time domain signal with the particle transform coefficients. Its calculation formula is as follows.(7)ft=1Cφ∫−∞+∞∫−∞+∞CWTa,bEa,btdadba2.


### 3.8. Discrete Wavelet Function

Because the continuous wavelet transform has continuity, it needs to be discretized in the practical application of the computer. The calculation formula of the discretized wavelet function is shown below.(8)Εj,kt=a−j/20Εt−ka0ja0j.


### 3.9. Split Index

The SPRINT algorithm uses the Gini index as the segmentation criterion. For attribute selection criteria, the Gini index algorithm takes the purity of the dataset as the attribute selection criteria. The formula for calculating the Gini index of nodet is
(9)Gt=1−∑i=0G−1Pit2.


### 3.10. Cluster Head Algorithm

In the cluster head selection step, a random number between 0 and 1 is the basis of the cluster head noden. The threshold T is
(10)Tn=p1−p×m1/pn∈G0.


### 3.11. Classification of Intelligence Level

According to the heterogeneous characteristics of IoT nodes, it classifies the intelligence level of nodes. It treats a high-intelligence node as the sum of multiple low-intelligence nodes, increasing the probability of a high-intelligence node becoming the head. The intelligence level of the node is defined in the randomly distributed intervalW,amaxW. amax is a multiple of the ratio of the nodes with the highest intelligence level to the nodes with the lowest intelligence level. For any node si, its intelligence is αiW. So the total intelligence is
(11)W=∑j=1N∂jW.


### 3.12. Detection Probability Model

(12)px,y=e−ad.a is the physical property of the sensor. IoT is assumed to be a wireless sensor network with n sensors. The weighting factors for each sensor are W1, W2…. Here, x=1,2,3⋯n, y=1,2,3⋯m, and m is the similarity algorithm for the number of monitoring targets.
(13)S=∑i=1aAiBi∑i=1aAi2∑i=1aBi2.


### 3.13. Hash Algorithm

The hash algorithm has the advantage of fast lookup time, and the formula is shown in (14).
(14)Hi=Hi−1×x+si.


### 3.14. Classical Information Theory

(15)w=p×log21P+q×log21P.Among them,p is the probability that a given item identifier obeys the rules, and q is the probability that it does not conform to the rules.


### 3.15. Signal Strength Algorithm

(16)‐S=1n∑i=1nSi.Among them,Si represents the signal strength of each node, and n represents the number of hops. S represents the average signal degree on the entire path, and the larger the S of the path, the more reliable the path is.


### 3.16. Signal Gap Algorithm

(17)D2=1n∑i=1nSi−−S2.The formula represents the size of the gap between the signal strengths of each node on a path. The smaller D2 is, the better the signal strength distribution of the nodes on the path is.


### 3.17. Fitness Function

(18)Fyi=1n∑j=1nOi−Tj2.In the formula,Oi,Ti is the jth predicted output and actual output, and n is the total amount of data.


### 3.18. ACO Algorithm

The ACO algorithm is a swarm intelligence algorithm. When simulating foraging ants, the ants choose the walking direction according to the pheromone concentration and plan the optimal path.(19)yi=1m∑j=1mOj−Tj2.


## 3.1. Network Throughput

The data in the network is composed of data packets, and the processing of each data packet by the firewall consumes resources. Throughput is the maximum rate a device can accept without frame loss. The test method is as follows: send a certain number of frames at a certain rate during the test, and calculate the frames transmitted by the device under test. If the number of frames sent is equal to the number of frames received, then the sending rate and retest are increased; if the frame is received, if there are fewer than sending frames, reduce the sending rate and retest until the final result is obtained. Throughput test results are expressed in bits per second or bytes per second.Network throughput [20] is an important metric used in many grid experiments. It represents the sending process from the beginning of sending data information to the destination node in the continuous process of a node or unit in the running mode. It is shown in the following:
(1)th=pkt_byte_sumxend_timex−timex−1×8/100.Among them,th is the throughput of the network, pkt_byte_sumx is the size of the data packet sent by process x, end_timex is the time when process j receives the data packet, and end_timej−1 is the time of the last received packet.


## 3.2. Membership

In the normal cloud model, the degree of membership obeys a normal distribution with expected entropyEn and farsightedness He as standard deviations, i.e., NEn,He2, which satisfies the degree of participation from x to C.
(2)μx=exp−x−Ex22En′2.x is the actual value, En′ obeys the En′~NEn,He2 distribution, and the value of He is smaller than the value of En. Therefore, when calculating μx, En can be used instead of En′.


## 3.3. Combinatorial Optimization Problem

Combinatorial optimization [21] is an optimization problem that studies different variables. The knapsack problem is an important part of the overall optimization, and it is also the most studied problem in the current overall optimization problem. The knapsack problem is how to choose within a limited total volume to maximize the total value of items. It can be formulated as a linear program as follows:
(3)KPmax∑m=1npmxms,t∑m=1nwmxm≤cxm∈0,1x=1..⋯,n.n is the number of items, and pi, mx, and m∈N=1,⋯,n are the value and weight of item m, respectively. c is a positive integer and is the capacity of the knapsack.


## 3.4. Wavelet Transform Function

Wavelet transform is a new transform analysis method. It inherits and develops the idea of localization of short-time Fourier transform, at the same time, overcomes the shortcomings of window size that does not change with frequency, can provide a “time-frequency” window that changes with frequency, and is an ideal tool for signal time-frequency analysis and processing.(4)Ea,bt=1aEt−ba.E is the wavelet function.


## 3.5. Wavelet Packet Function

(5)CE=2π∫−∞+∞Εφ2φdt<∞.


## 3.6. Continuous Wavelet Transform (CWT) Function

The CWT function is a transformation method proposed on the basis of the short-time Fourier transform. Its definition is shown in the following formula.(6)CWTa,b=∫−∞+∞ftΕa,btdt.


## 3.7. Continuous Wavelet Inverse Transform

The continuous inverse particle transform can reconstruct the time domain signal with the particle transform coefficients. Its calculation formula is as follows.(7)ft=1Cφ∫−∞+∞∫−∞+∞CWTa,bEa,btdadba2.


## 3.8. Discrete Wavelet Function

Because the continuous wavelet transform has continuity, it needs to be discretized in the practical application of the computer. The calculation formula of the discretized wavelet function is shown below.(8)Εj,kt=a−j/20Εt−ka0ja0j.


## 3.9. Split Index

The SPRINT algorithm uses the Gini index as the segmentation criterion. For attribute selection criteria, the Gini index algorithm takes the purity of the dataset as the attribute selection criteria. The formula for calculating the Gini index of nodet is
(9)Gt=1−∑i=0G−1Pit2.


## 3.10. Cluster Head Algorithm

In the cluster head selection step, a random number between 0 and 1 is the basis of the cluster head noden. The threshold T is
(10)Tn=p1−p×m1/pn∈G0.


## 3.11. Classification of Intelligence Level

According to the heterogeneous characteristics of IoT nodes, it classifies the intelligence level of nodes. It treats a high-intelligence node as the sum of multiple low-intelligence nodes, increasing the probability of a high-intelligence node becoming the head. The intelligence level of the node is defined in the randomly distributed intervalW,amaxW. amax is a multiple of the ratio of the nodes with the highest intelligence level to the nodes with the lowest intelligence level. For any node si, its intelligence is αiW. So the total intelligence is
(11)W=∑j=1N∂jW.


## 3.12. Detection Probability Model

(12)px,y=e−ad.a is the physical property of the sensor. IoT is assumed to be a wireless sensor network with n sensors. The weighting factors for each sensor are W1, W2…. Here, x=1,2,3⋯n, y=1,2,3⋯m, and m is the similarity algorithm for the number of monitoring targets.
(13)S=∑i=1aAiBi∑i=1aAi2∑i=1aBi2.


## 3.13. Hash Algorithm

The hash algorithm has the advantage of fast lookup time, and the formula is shown in (14).
(14)Hi=Hi−1×x+si.


## 3.14. Classical Information Theory

(15)w=p×log21P+q×log21P.Among them,p is the probability that a given item identifier obeys the rules, and q is the probability that it does not conform to the rules.


## 3.15. Signal Strength Algorithm

(16)‐S=1n∑i=1nSi.Among them,Si represents the signal strength of each node, and n represents the number of hops. S represents the average signal degree on the entire path, and the larger the S of the path, the more reliable the path is.


## 3.16. Signal Gap Algorithm

(17)D2=1n∑i=1nSi−−S2.The formula represents the size of the gap between the signal strengths of each node on a path. The smaller D2 is, the better the signal strength distribution of the nodes on the path is.


## 3.17. Fitness Function

(18)Fyi=1n∑j=1nOi−Tj2.In the formula,Oi,Ti is the jth predicted output and actual output, and n is the total amount of data.


## 3.18. ACO Algorithm

The ACO algorithm is a swarm intelligence algorithm. When simulating foraging ants, the ants choose the walking direction according to the pheromone concentration and plan the optimal path.(19)yi=1m∑j=1mOj−Tj2.


## 4. International Trade Industry Development Policy Process

Since this paper is a research on the development policy of the international trade industry based on the background of cloud computing and the Internet of Things, it is difficult to conduct questionnaire surveys and interviews in the field to obtain specific survey data. The main research method of this paper is to conduct relevant data queries on the Internet. With the proposal and continuous construction of the “One Belt, One Road” plan, the international trade industry is constantly faced with opportunities and challenges. The various development policies proposed in the Belt and Road Initiative to seize opportunities and meet challenges also apply to the development of international trade. It inquired about the “Belt and Road” construction and development policies and searched for the fiscal policy, financial policy, investment and trade cooperation policy, customs policy, and transportation policy in the past seven years. It integrates data, conducts research on the development policy of the international trade industry, and conducts a summary analysis [22, 23].


## 5. Results of the International Trade Industry Development Policies

Today is the era of cloud computing, and international business still faces some challenges. Only by constantly researching and developing policies can we seize opportunities and anticipate challenges and make the international market invincible. In addition, in the context of the Internet of Things, if the international trade industry wants to develop better, it must learn to analyze and use the relevant development policy data provided by cloud computing [24]. In order to better study development policies in the context of cloud computing and the Internet of Things, this paper studies and analyzes international trade data from 2015 to 2021.


### 5.1. Fiscal and Tax Payment Policies in the Context of Cloud Computing and IoT

In the construction of the international trade industry, the fiscal policy can play a very key positive role, and the fiscal and tax payment policy is an important part of the fiscal policy [25]. In order to examine the effect of fiscal and tax payment policies on the international trade industry, this paper selects relevant data from 2015 to 2021. The specific data is shown in Figure 6.Figure 6
Fiscal and tax payment policies in the context of cloud computing and IoT.As can be seen from Figure6, from 2015 to 2021, in order to support the development of the international trade industry, the amount of government taxes on it has decreased year by year, while the amount of expenditure and national income distribution has continued to increase. In addition, in order to strengthen the infrastructure construction of the international trade industry, its budgetary and extrabudgetary expenditures on international trade are also increasing. The biggest purpose of increasing financial investment and financial subsidies is to promote the prosperity and development of the international trade industry [26]. Through data analysis, it can be seen that the fiscal and tax payment policy in the context of cloud computing and the Internet of Things can greatly promote the economic development of the international trade industry.


### 5.2. Financial Payment Policy in the Context of Cloud Computing and IoT

The construction of the international trade industry requires a lot of financing support, and cooperation with other countries will also form a large amount of currency circulation [27]. The financial payment policy in the context of cloud computing and the Internet of Things provides strong support for the financing of the international trade industry. The specific data is shown in Figure 7.Figure 7
Financial payment policies in the context of cloud computing and IoT.As can be seen from Figure7, in the financial payment policy in the context of cloud computing and the Internet of Things, in order to better support the financing of the international trade industry, the statutory reserve ratio continues to decrease. The proportion of open market business has increased year by year, and the exchange rate has fluctuated and developed with the changes in the international situation. In addition, the interest rate of demand deposits in recent years has been significantly lower than the interest rate of time deposits. It increases household savings and increases financing for the international trade industry. Through data analysis, it can be seen that the financial payment policy in the context of cloud computing and the Internet of Things plays an important role in industrial financing [28, 29].


### 5.3. Investment and Trade Cooperation Policies in the Context of Cloud Computing and IoT

Investment and trade cooperation is an important means to promote the construction of the international trade industry and plays a very important role. Investment and trade cooperation requires all parties to study and solve investment and trade facilitation issues, eliminate investment and trade barriers, build a good business environment, jointly negotiate the construction of free trade zones, stimulate and release cooperation potential, and promote trade development. The investment and trade cooperation policy in the context of cloud computing and IoT is shown in Figure8.Figure 8
Investment and trade cooperation policies in the context of cloud computing and IoT.It can be seen from Figure8 that the investment and trade cooperation policy in the context of cloud computing IoT can provide the international trade industry with trade information of various neighboring countries. It allows the industry to choose partners independently. Among them, Singapore and Russia are countries that can cooperate deeply. India and Thailand are countries that can accelerate cooperation. The Philippines and Poland are countries that can gradually expand cooperation. Countries to be strengthened are like Mongolia and Egypt. However, a higher cooperation index does not mean a higher trade potential and level. Factors such as trade environment and risks should also be considered. The investment and trade cooperation policy in the context of cloud computing and IoT can reasonably avoid trade risks for the international trade industry, strengthen international cooperation, and promote trade development.


### 5.4. Customs Support Policies in the Context of Cloud Computing and IoT

The proposal of the customs support policy also has a very important role and significance for the development of the international trade industry. The comparative data before and after the customs payment policy is shown in Figure9.Figure 9
Comparative data before and after the customs payment policy.As can be seen from Figure9, the data comparison before and after the customs payment policy is very obvious. Before the customs payment policy was proposed, the processing efficiency of the annual trial plan of the international trade industry was only about 50%. After the policy was proposed, the handling efficiency of the annual trial plan can reach more than 80%, which greatly facilitates the handling of the annual trial plan of the international trade industry. In addition, smooth channels, cooperation opportunities, and the construction of training centers have all been greatly improved after the customs payment policy was proposed, which has promoted the facilitation of international trade.


### 5.5. Transportation Support Policies in the Context of Cloud Computing and IoT

Supporting transportation is key to the rapid development of the international trade industry. Only by continuously developing and paying for transportation and proposing special transportation support policies can international trade really play a role in promoting economic development along the coast. The specific data is shown in Figure10.Figure 10
Construction results of transportation support policies.It can be seen from the data in Figure10 that from 2015 to 2021, the construction rate of railways and highways has been increasing. This shows that today’s transportation infrastructure is constantly being improved, greatly improving the transportation efficiency of the international trade industry. In addition, in the transportation support policy in the context of cloud computing and the Internet of Things, the prediction accuracy of direction is as high as 60%. It can facilitate the international trade industry to choose the mode of transportation according to their needs.


## 5.1. Fiscal and Tax Payment Policies in the Context of Cloud Computing and IoT

In the construction of the international trade industry, the fiscal policy can play a very key positive role, and the fiscal and tax payment policy is an important part of the fiscal policy [25]. In order to examine the effect of fiscal and tax payment policies on the international trade industry, this paper selects relevant data from 2015 to 2021. The specific data is shown in Figure 6.Figure 6
Fiscal and tax payment policies in the context of cloud computing and IoT.As can be seen from Figure6, from 2015 to 2021, in order to support the development of the international trade industry, the amount of government taxes on it has decreased year by year, while the amount of expenditure and national income distribution has continued to increase. In addition, in order to strengthen the infrastructure construction of the international trade industry, its budgetary and extrabudgetary expenditures on international trade are also increasing. The biggest purpose of increasing financial investment and financial subsidies is to promote the prosperity and development of the international trade industry [26]. Through data analysis, it can be seen that the fiscal and tax payment policy in the context of cloud computing and the Internet of Things can greatly promote the economic development of the international trade industry.


## 5.2. Financial Payment Policy in the Context of Cloud Computing and IoT

The construction of the international trade industry requires a lot of financing support, and cooperation with other countries will also form a large amount of currency circulation [27]. The financial payment policy in the context of cloud computing and the Internet of Things provides strong support for the financing of the international trade industry. The specific data is shown in Figure 7.Figure 7
Financial payment policies in the context of cloud computing and IoT.As can be seen from Figure7, in the financial payment policy in the context of cloud computing and the Internet of Things, in order to better support the financing of the international trade industry, the statutory reserve ratio continues to decrease. The proportion of open market business has increased year by year, and the exchange rate has fluctuated and developed with the changes in the international situation. In addition, the interest rate of demand deposits in recent years has been significantly lower than the interest rate of time deposits. It increases household savings and increases financing for the international trade industry. Through data analysis, it can be seen that the financial payment policy in the context of cloud computing and the Internet of Things plays an important role in industrial financing [28, 29].


## 5.3. Investment and Trade Cooperation Policies in the Context of Cloud Computing and IoT

Investment and trade cooperation is an important means to promote the construction of the international trade industry and plays a very important role. Investment and trade cooperation requires all parties to study and solve investment and trade facilitation issues, eliminate investment and trade barriers, build a good business environment, jointly negotiate the construction of free trade zones, stimulate and release cooperation potential, and promote trade development. The investment and trade cooperation policy in the context of cloud computing and IoT is shown in Figure8.Figure 8
Investment and trade cooperation policies in the context of cloud computing and IoT.It can be seen from Figure8 that the investment and trade cooperation policy in the context of cloud computing IoT can provide the international trade industry with trade information of various neighboring countries. It allows the industry to choose partners independently. Among them, Singapore and Russia are countries that can cooperate deeply. India and Thailand are countries that can accelerate cooperation. The Philippines and Poland are countries that can gradually expand cooperation. Countries to be strengthened are like Mongolia and Egypt. However, a higher cooperation index does not mean a higher trade potential and level. Factors such as trade environment and risks should also be considered. The investment and trade cooperation policy in the context of cloud computing and IoT can reasonably avoid trade risks for the international trade industry, strengthen international cooperation, and promote trade development.


## 5.4. Customs Support Policies in the Context of Cloud Computing and IoT

The proposal of the customs support policy also has a very important role and significance for the development of the international trade industry. The comparative data before and after the customs payment policy is shown in Figure9.Figure 9
Comparative data before and after the customs payment policy.As can be seen from Figure9, the data comparison before and after the customs payment policy is very obvious. Before the customs payment policy was proposed, the processing efficiency of the annual trial plan of the international trade industry was only about 50%. After the policy was proposed, the handling efficiency of the annual trial plan can reach more than 80%, which greatly facilitates the handling of the annual trial plan of the international trade industry. In addition, smooth channels, cooperation opportunities, and the construction of training centers have all been greatly improved after the customs payment policy was proposed, which has promoted the facilitation of international trade.


## 5.5. Transportation Support Policies in the Context of Cloud Computing and IoT

Supporting transportation is key to the rapid development of the international trade industry. Only by continuously developing and paying for transportation and proposing special transportation support policies can international trade really play a role in promoting economic development along the coast. The specific data is shown in Figure10.Figure 10
Construction results of transportation support policies.It can be seen from the data in Figure10 that from 2015 to 2021, the construction rate of railways and highways has been increasing. This shows that today’s transportation infrastructure is constantly being improved, greatly improving the transportation efficiency of the international trade industry. In addition, in the transportation support policy in the context of cloud computing and the Internet of Things, the prediction accuracy of direction is as high as 60%. It can facilitate the international trade industry to choose the mode of transportation according to their needs.


## 6. Results of the International Trade Industry Development Policy

With the continuous development of the economy, cloud computing and the Internet of Things are getting more and more attention. Due to the multiple advantages of cloud computing and the Internet of Things, they have also been widely used in China and are suitable for use in various industries. Especially in the process of international trade development, the application of cloud computing and Internet of Things technology can make development policies meet the needs of the international trade industry to the greatest extent. Accordingly, this paper examines the development policies of the international trade industry in the context of cloud computing and the Internet of Things. The investigation has certain practical significance.(1)
Fiscal and taxation support policies in the context of cloud computing and the Internet of Things. Through the transportation support policy, a tax-related information sharing platform covering various regions, customs, economic, and trade departments can be established. It strengthens the monitoring of tax sources, timely reminds the trade industry of abnormal water wading, and helps the industry to reasonably avoid tax risks. At the same time, it increases investment and subsidies for the construction of the international trade industry through expansionary fiscal policies, expands the scale of international trade, and promotes economic development(2)
Financial support policies in the context of cloud computing and IoT. Financial support policies can not only play a fundamental and decisive role in the allocation of market resources but also respond to the financial needs of the international trade industry during the development process. Making good use of the financial support policy in the context of cloud computing and the Internet of Things can provide strong financial support for the international trade industry(3)
Supporting policies for investment and trade cooperation in the context of cloud computing and Internet of Things. Investment and trade cooperation support policies play an important role in improving the level of trade liberalization and facilitation. It strengthens cooperation on supply chain security and facilitation, reduces nontariff barriers, and lays a solid foundation for deepening bilateral and multilateral cooperation(4)
Customs support policy in the context of cloud computing IoT. The customs support policy can further strengthen the cooperation between international customs, realize the interconnection between international customs, effectively promote trade facilitation, and promote the process of regional economic development. In addition, the customs support policy also gives priority to the annual trial plan of the regions along the international trade route. This facilitates the international trade industry to innovate and enrich cooperation mechanisms and strengthen security cooperation with customs of countries along the route(5)
Transportation support policies in the context of cloud computing and the Internet of Things. Transportation plays a key role in supporting economic development. The proposal of the transportation support policy has laid a strong foundation for promoting the construction of interconnected transportation infrastructure and the construction of the Maritime Silk Road Corridor. In addition, transportation policy supports the internationalization and integration of transportation services in addition to supporting large transportation projects and node construction. It actively develops transport service trade and promotes the development of international trade economy


## 7. Conclusion

The development policy of the international trade industry is directly related to the overall development of international trade. It plays an important role in promoting the development of the national economy and enhancing the regional economic capacity of the region. This paper studies the industrial development policy of international trade in the context of cloud computing and the Internet of Things and actively explores effective measures to promote the development of global trade. By promoting the development policy of high-tech enterprises, it will transform the development of the international trade industry from small-scale development to large-scale development and comprehensively transform the economic system in the field of international trade. Actively building the development policy of the international trade legal system is the most basic condition to ensure the smooth flow of international trade. Only by actively building an international trade legal system can we create opportunities for global business development and create a better environment for the global market. In addition, development policies that formulate trade strategies can promote healthy and rapid growth in international trade. If it is to trade globally, it must comply with international standards. It is necessary to study global trade rules, improve the quality of certain services according to customs, and actively explore new markets for international trade. At the same time, it is necessary to deepen economic exchanges between countries through regional cooperation, strengthen relations between countries, and lay a solid foundation for long-term cooperation. Through its many regional partners, it can continue to open its markets to international trade, which to a certain extent diversifies international trade. In the future international trade, in addition to actively participating in global trade, it is necessary to formulate environmental trade standards, expand interregional cooperation, and maintain cooperation with developing countries in the region.



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*Source: 6313339-2022-06-02.xml*