1 Introduction

Mobile edge computing, while adopting a new generation of distributed optimization strategies such as stable matching. Cache technology can meet the needs of users under peak traffic load and reduce the load of wireless and backhaul resources. The combination of MEC and UDRN can not only deal with access from mass communication equipment, but also provide powerful computing capabilities for users at the edge of the wireless network. MEC-based UDRN can effectively handle computationally intensive and data-intensive tasks. This article aims to guide doctors to adjust their mentality, strengthen goals, rebuild habits, help them resolve negative emotions as soon as possible, and establish new coronary pneumonia epidemic medical staff, pharmacy and basic medicine personnel A case library of advanced deeds education materials, to create an epidemic case classroom combining specific cases with professional knowledge of Chinese medicine, as a professional course of Chinese medicine. Through careful curriculum design and implementation, the effect of turning crises into opportunities is achieved. The purpose of enhancing doctors’ love for the cause of Chinese medicine, enhancing the national pride and self-confidence of doctors in Chinese medicine colleges, stabilizing the psychological state of doctors, and restoring an optimistic and active learning state as soon as possible. Cloud database is a new software service under the continuous development of software as a service. Compared with traditional databases, cloud database has the advantages of cloud computing on-demand allocation, dynamic expansion, and maintenance-free management. At present, domestic IT giants have launched cloud database services in public cloud environments, but for an enterprise, it is more hoped to use database services in private clouds. However, there are few cloud database service system solutions in private cloud environments. Therefore, this article combines the existing cloud platform in the laboratory, studies and compares the automatic deployment frameworks of SaltStack and Ansible, and designs a solution for building a mysql cloud database service system under the laboratory's private cloud platform. This paper first divides the limited character input UDRN into multiple clusters through the K-means algorithm, and then uses the golden section method to obtain the optimal amount of power purchased by the user from the relay, thereby maximizing the utility function of the user node. Then, the mutual preference matrix between the user and the relay is established, and a utility-based stable matching algorithm for the limited character input EH relay network is proposed, which aims to derive the sub-optimal utility optimization scheme of the network. Finally, analyze the practicality, convergence, complexity and communication overhead of the algorithm.

2 Related work

Literature [1] shows that as cloud computing technology continues to mature, more and more manufacturers invest in the research and development of cloud applications, among which the database, as an indispensable basic resource in various applications, has an important position in the application system. Literature [2] pointed out that the cloud will dominate the future of the database market. By 2022, 75% of the databases will be deployed or migrated to the cloud platform, and only 5% of the databases will be considered for local deployment. The literature [3] shows that the research of cloud database has broad prospects. The application of cloud computing is also the inevitable result of the continuous development of cloud computing technology and the database is the foundation of much application software. For small and medium-sized enterprises, enterprise users can quickly build various database-related applications on the Web to achieve overall management of the enterprise. For large enterprises, building a cloud database reduces the cost of enterprise data management resources. Migrating from a data center to a cloud database has become a data management trend. Literature [4] indicates that the development prospects of cloud databases are very broad, which has driven the innovation and development of the database field. With the popularity of cloud service models, database as a service is being widely concerned and recognized. It allows users to no longer be distracted by database deployment and management, and focus all their energy on their core business. Moreover, the demand for data storage by enterprises has been increasing year by year, and the demand for physical resources by applications has also shown a trend of dynamic changes. Traditional relational databases have been difficult to meet the needs of users. Therefore, it is of great significance to the research of cloud database. It is based on this background that this article combines the laboratory cloud platform to carry out the research of cloud database service system. Literature [5] shows that with the development of the world economy and the development of information and communication technology, the number of subscriptions for mobile cellular and mobile broadband services has greatly increased. Fading is the most important problem in wireless networks, so ultra-dense networks are one of the ways to solve the problem. Literature [6] pointed out that the macro extended AP can effectively extend the signal coverage of the base station. Considering the occasional burst traffic load, compared with the inflexible base station deployment scheme, the relay deployment scheme can quickly respond to the capacity improvement requirements. Therefore, in the research of next-generation wireless networks, ultra-dense relay networks have become a new research focus. Compared with traditional networks, the advantages of deploying UDRN are as follows: (1) Better coverage: Because the relay, source node and destination node are very close, and the relay can receive and forward the source node's information, it is outdoor Or dense deployment of relays in indoor environments will expand the coverage of BS and improve the effects of fading, path loss, shadow, small coverage, and low signal-to-noise ratio; (2) Enhanced capacity: dense deployment of relays will enhance the network the capacity to improve bandwidth availability, SE and EE. Because the relay transmits at lower power, it reduces interference and achieves a higher signal-to-interference to noise ratio. (3) Higher reliability: By transferring the indoor hotspot traffic to the relay, the traffic congestion of the BS can be reduced, thereby making the BS more reliable. Moreover, the offloading of traffic from the BS to the relay improves the overall network performance and service [7].

3 Edge computing and cloud service data system

3.1 Edge computing

3.1.1 System model

This paper considers an EH-based UDRN. As shown in Fig. 1, the system model consists of S user nodes, N relay nodes and a BSD. Here, the user and the BS also refer to the source node and the destination node respectively. S user nodes and N relay nodes in the network are represented by the set μ, ν respectively. The relay node adopts the DF strategy, assuming that the destination node has a continuous energy supply, and the relay node relies on the collected energy to transmit signals [8].

Fig. 1
figure 1

UDRN system model

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The transmission time slot can be expressed by τ = 1, and the received signal at the destination node d and the relay k can be expressed as Eqs. (1) and (2) respectively:

$$ y_{{i,d}} = \sqrt {p_{i} h_{{i,d}} } x_{i} + n_{{i,d}} $$
(1)

With:

$$ y_{{i,k}} = \sqrt {p_{i} h_{{i,k}} } x_{i} + n_{{i,k}} $$
(2)

In stage 2, the relay k ∈ ν selected by user i regenerates the received signal, and forwards the estimated symbol to the destination node d with the transmit power, then the following formula (3):

$$ y_{{k,d}} = \sqrt {p_{{i,k}} } h_{{k,d}} x_{i} + n_{{k,d}} $$
(3)

Due to the limited capacity of the battery, the energy collected by the relay must meet the constraints, and there will be no energy overflow. The energy storage constraint of the limited battery is Eq. (4):

$$ E_{k}^{s} = \min \left( {E_{k}^{0} + E_{k}^{{EH}} ,E_{k}^{{tol}} } \right) $$
(4)

3.1.2 Utility optimization strategy based on resource allocation

In the UDRN scenario, interference is a serious problem, and it is difficult to access the state information of all nodes in the network to optimize system performance, and the optimization algorithm has high computational complexity. Therefore, this paper adopts a clustering scheme. First, all nodes are divided into C clusters, and then the optimization strategy is executed in one cluster. Due to the high efficiency and simplicity of the K-means algorithm, the K-means algorithm is used to determine each cluster member and the node closest to the centroid is selected as the cluster head. In order to make a trade-off between resource utilization efficiency and interference reduction, resources are orthogonal within clusters and reused between clusters [9]. Inter-cluster interference can be eliminated by orthogonal resource allocation schemes, such as orthogonal frequency division multiple access. Considering the inter-cluster interference, SINRs can be expressed as formulas (5), (6), (7):

$$ \gamma _{{i,d}} = \frac{{p_{i} \left| {h_{{i,k}} } \right|^{2} }}{{\sigma ^{2} + I_{{i,k}} }} $$
(5)
$$ \gamma _{{i,d}} = \frac{{p_{i} \left| {h_{{i,d}} } \right|^{2} }}{{\sigma ^{2} + I_{{i,d}} }} $$
(6)
$$ \gamma _{{k,d}} = \frac{{p_{{i,k}} \left| {h_{{k,d}} } \right|^{2} }}{{\sigma ^{2} + I_{{k,d}} }} $$
(7)

Therefore, the maximum ratio combination can be expressed as (8):

$$ \gamma _{{i,k,d}} = \min \left( {\gamma _{{i,k}} ,\gamma _{{i,d}} + \gamma _{{k,d}} } \right) $$
(8)

The reachable information rate of the output of the MRC with limited character input can be expressed as formula (9):

$$ R_{{i,d,k}} \left( {p_{{i,k}} } \right) = \frac{1}{2}\log _{2} M - \frac{1}{{2M}}\sum\limits_{{m = 1}}^{M} {\log _{2} \sum\limits_{{n = 1}}^{M} {\exp \left( {g_{{mn}} \left( {p_{{i,k}} } \right)} \right)} } $$
(9)

The user is modeled as an energy purchaser, and the acquisition rate and consumption expenditure are considered comprehensively, so the utility function of user i is Eq. (10):

$$ U_{{i,k}}^{u} \left( {p_{i} ,k} \right) = g_{i} R_{{i,k,d}} \left( {p_{{i,k}} } \right) - \eta _{k} p_{{i,k}} $$
(10)

Modeling relays as energy sellers aims to maximize their own profits. Considering the sales revenue, the utility function of the relay k ∈ ω can be defined as formula (11):

$$ U_{{i,k}}^{r} \left( {p_{i} ,k} \right) = (\eta _{k} - c_{k} )p_{{i,k}} $$
(11)

Considering the fairness between user i and relay k, the utility function of the matching pair can be expressed as Eq. (12):

$$ \begin{aligned} U_{{i,k}}^{N} \left( {p_{i} ,k} \right) &= {\text{w}}^{u} U_{{i,k}}^{u} \left( {p_{{i,k}} } \right) + {\text{w}}^{r} U_{{i,k}}^{r} (p_{{i,k}} ) \hfill \\ & = {\text{w}}^{u} (g_{i} R_{{i,k,d}} - \eta _{k} p_{{i,k}} ) + {\text{w}}^{r} (\eta _{k} - c_{k} )p_{{i,k}} \hfill \\ \end{aligned} $$
(12)

The energy consumption of the matched pair is Eq. (13):

$$ E_{{i,k}} \left( {{\text{p}}_{{i,k}} } \right) = \frac{1}{2}\tau p_{i} + \frac{1}{2}\tau p_{{i,k}} $$
(13)

Among them, the first item and the second item respectively represent the energy consumption of the user and the relay during the cooperative transmission of a data block. Define EE as the ratio of utility to energy consumption, then the EE of the matched pair is Eq. (14):

$$ U_{{{\text{i}},k}}^{{EE}} \left( {p_{{i,k}} } \right) = \frac{{U_{{i,k}}^{N} \left( {p_{{i,k}} } \right)}}{{E_{{i,k}}^{{}} \left( {p_{{i,k}} } \right)}} $$
(14)

Following the other constraint of k buying power is as shown in Eq. (15):

$$ \frac{1}{2}\tau {\text{p}}_{k}^{{\max }} \le E_{k}^{s} $$
(15)

The utility of user i am maximized as shown in formulas (16), (17), (18):

$$ \mathop {\min }\limits_{{p_{{i,k}} }} - U_{{i,k}}^{u} \left( {p_{{i,k}} } \right) = - g_{i} R_{{i,k,d}} + \eta _{k} p_{{i,d}} $$
(16)
$$ s.t.0 \le \frac{{p_{{i,k}} }}{2} \le E_{k}^{s} $$
(17)
$$ E_{k}^{s} = \min \left( {E_{k}^{0} + E_{k}^{{EH}} ,E_{k}^{{tol}} } \right) $$
(18)

The optimal amount of power purchased from relay k can be given by Eq. (19):

$$ p_{{i,k}}^{*} = \mathop {\arg \max }\limits_{{p_{{i,k}} }} \left( {U_{{i,k}}^{u} \left( {p_{{i,k}} } \right)} \right) $$
(19)

Study the one-to-one matching between the user and the relay. If a user cannot match the relay, that is, T > K, it sends the information directly to the destination node. The utility between the user and the target node d can be calculated by the following formula (20):

$$ \begin{aligned} U_{{i,d}}^{u}& = g_{i} R_{{i,d}} \\ &= g_{i} (\log _{2} M - \frac{1}{M}\sum\limits_{{n = 1}}^{M} {\exp \left( {g_{{mn}} \left( {p_{i} } \right)} \right))} \end{aligned} $$
(20)

And energy consumption can be expressed as formula (21):

$$ E_{{i,d}} \left( {p_{{i,k}} } \right) = \tau p_{i} $$
(21)

The matching matrix Θ of the system can be expressed as formula (22):

$$ \left[ \Theta \right]_{{{\text{i,k}}}} = \left\{ \begin{gathered} 1,match\;the\;user\;i\;and\;relay\;k \hfill \\ 0,otherwise \hfill \\ \end{gathered} \right.,\forall i \in x,\forall k \in \omega $$
(22)

The utility function matrix of all users can be expressed as formula (23):

$$ U^{u} = \left[ {U_{1}^{u} ,\dots,U_{T}^{u} } \right]^{T} $$
(23)

Similarly, the utility function matrix of all relays can be expressed as Eq. (24):

$$ U^{{\text{r}}} = \left[ {U_{1}^{r} ,\dots,U_{K}^{r} } \right]^{T} $$
(24)

According to the establishment of the utility function matrix, the matching problem to maximize the utility of the matching pair is as shown in Eqs. (25), (26), (27):

$$ \mathop {\max }\limits_{\Theta } (w^{u} Tr\left( {\Theta \left( {U^{u} } \right)^{T} } \right) + w^{r} Tr\left( {U^{r} \Theta } \right) $$
(25)
$$ s.t.\sum\limits_{{k = 1}}^{K} {\left[ \Theta \right]} _{{i,k}} = 1,1 \le i \le T $$
(26)
$$ \sum\limits_{{i = 1}}^{T} {\left[ \Theta \right]} _{{i,k}} = 1,1 \le k \le K $$
(27)

The preferences of all users can be expressed as formula (28):

$$ P^{{\text{u}}} = \left[ {P_{1}^{u} ,\dots,P_{i}^{u} ,\dots,P_{T}^{u} } \right]^{T} $$
(28)

Similarly, there is formula (29):

$$ P^{{\text{r}}} = \left[ {P_{1}^{r} ,\dots,P_{k}^{r} ,\dots,P_{K}^{r} } \right]^{T} $$
(29)

After the preference matrix is established, a stable matching algorithm based on the GS algorithm can be obtained. When each user matches a certain relay or has been rejected by all relays, the algorithm ends, that is, when the following conditions are true, the user and the result of stable matching between relays is (30):

$$ rank\left( \Theta \right) = L $$
(30)

The total signaling overhead can be obtained by formula (31):

$$ \Omega _{{pro}} = \left( {K + 1} \right)N_{T} + KN_{H} + KN_{I} + K_{M} \left( {3N_{A} + 4N_{B} + 2N_{C} } \right) $$
(31)

According to the percentage of signaling transmission time and channel coherence time to characterize communication overhead, the formula is given by the following formula (32):

$$ \Omega _{{per}} = \frac{{\Omega _{{pro}} }}{{IT_{c} }} $$
(32)

3.1.3 Simulation results

In this paper, the performance of the stable matching algorithm of the ultra-dense EH relay network with limited character input is studied, and the performance of the proposed matching algorithm is compared with other schemes. The simulation system is divided into an actual system with limited character input and a hypothetical system based on Gaussian input. The matching algorithm is divided into a stable matching algorithm, a shortest distance matching algorithm and a random matching algorithm [10]. For the sake of simplicity, the scheme is shown in Table 1 below:

Table 1 UDRN simulation parameters
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The experimental results are mainly divided into three parts: First, compare and evaluate the impact of user power on performance. Second, compare and evaluate the impact of price factors on performance. Finally, compare and evaluate the communication overhead and execution time of the proposed algorithms. This paper considers the performance of the proposed stable matching algorithm from the perspective of the traversal utility of the matching pair of the system, EE and running time. User nodes and relay nodes are randomly distributed in the relay network with S = 60 and N = 140, and then the user nodes and relay nodes are divided into 5 clusters, as shown in Fig. 2.

Fig. 2
figure 2

Node distribution based on clustering

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First consider the impact of user power on performance, and set the user node power from 10 to 30dBm.

From these Figs. 3 and 4, we can first see that the curve trends of the five algorithms at QPSK and 16QAM input are almost the same, which shows the consistency in the power of the user node. It can also be observed that the utility of the matching pairs of all schemes increases with the increase of the user node power ip. This is because as the ip increases, the SINR increases, so the rate at the output of the MRC increases, and the system utility of the matching pair it also rises. In addition, a larger base M will also make the matching pair more effective, because a larger M provides more signal points included in the modulation signal constellation. It is also observed that the proposed SMP scheme can be effective. In the IP range of the whole test, the proposed SMP scheme obtains considerable performance improvement under QPSK and 16QAM input, which proves that the algorithm is superior to the other four schemes, and when the ip increases, the performance gain will become larger. Finally, it can be seen that if the RMA and SDA algorithms are directly applied to the limited self-character input system, it will cause severe performance loss. Among these five algorithms, the performance of the RMA algorithm is even the worst [11].

Fig. 3
figure 3

User power of matched pair under QPSK input

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Fig. 4
figure 4

User power of matched pair under 16QAM input

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Figure 5 shows the relationship between the EE of the matching pair and the power of the user node under different schemes. It can be seen that the performance of the proposed algorithm is better than the other four schemes within the tested ip range. For example, when pi = 30dbm, the performance of the proposed algorithm is 7.14%, 20.97%, 57.89% and 59.57% better than SDP, SDA, RMP and RMA, respectively.

Fig. 5
figure 5

Energy efficiency versus user power of a matched pair under QPSK input

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As shown in Fig. 6, it is observed that the utility of matching pairs of all schemes decreases as the price increases. There are two reasons: First, the unit price of power purchased by users increases as the price factor increases. In addition, users are willing to purchase less power to minimize their payment, which will reduce the speed and utility of limited character input matching pairs. It can also be observed that, within the tested range of πk, the proposed SMP scheme performs best, while RMA performs the worst. In addition, the SDP scheme provides the second best performance. The reason is that it considers statistical CSI that uses less actual system information, rather than complete CSI [12]. Moreover, the performance of the proposed scheme is much better than SDP, RMP, RMA and SDA schemes, especially when the base M is large, that is, when the input is 16QAM.

Fig. 6
figure 6

The traversal utility of matched pairs under QPSK input versus price factor

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3.2 Cloud service data system

3.2.1 Cloud service data system background

Cloud database is the development trend of database technology in the future. At present, there is no unified definition of cloud database. In this article, cloud database is a database deployed in a virtual computing environment. As SaaS applications gradually mature, it is applied to cloud platforms. The storage capacity of the database is enhanced, and the repeated configuration of personnel, hardware, and software is eliminated. Traditional databases meet the needs of user data management to a certain extent, but due to their own shortcomings and the rapid development of information technology, especially in the context of the management and application of massive data on cloud computing platforms, their disadvantages are becoming more and more obvious. The development of the database has gradually become the development direction of a new generation of databases. Compared with traditional databases, it solves the problems of high hardware cost, poor scalability, high management difficulty, slow business response, and low resource utilization [13]. The performance comparison between DBaaS and traditional self-built databases is shown in Table 2.

Table 2 DBaaS and traditional self-built database performance comparison table
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3.2.2 Comparison between SaltStack and Ansible

The following is a detailed comparison between SaltStack and Ansible in terms of performance and other aspects. The comparison table is shown in Table 3.

Table 3 Comparison table between SaltStack and Ansible
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Based on the above analysis and the scale of laboratory virtual machines, Ansible is more simple and convenient to use, has a lower learning and use cost, and can fulfill the needs of automated deployment of cloud database service systems. Therefore, this article selects Ansible as an automated deployment tool.

3.2.3 System database design

According to the analysis of system requirements and overall design, the following is to design the database table structure involved in each module of the cloud database service system. The virtual machine management module includes ordinary virtual machine tables and mysql virtual machine tables, storing basic information of ordinary virtual machines and mysql virtual machines. The E–R diagram between database tables is shown in Fig. 7 below.

Fig. 7
figure 7

Database E–R diagram

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Since there are too many design library tables involved in this article, only the more important table structures are described below, as shown in Table 4.

Table 4 Mysql virtual machine table
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The mysql virtual machine is created by the virtual machine template image, and the mysql database is also installed. When the mysql virtual machine is created by the administrator, the mysql virtual machine is installed by the ansible automated deployment tool, as shown in Table 5.

Table 5 Mirror table
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The mirror table saves the basic information of the mirror file of the ordinary virtual machine and the mirror file of the mysql virtual machine. A virtual machine is uniquely identified by image_type and template_id, which means that the mirror is created by this virtual machine. The location in the platform in order to use this image to create a new virtual machine. image_status indicates the status of the image, indicating whether the image is available, upload may be interrupted, and the upload is not completed, as shown in Table 6.

Table 6 Database instance table
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The database instance table records the configuration information of the virtual machine where the database instance is located, and returns information such as the ip required by the user to use the cloud database service and the database root account password.

4 Psychological reconstruction of doctors after the epidemic

4.1 The psychological impact of new coronary pneumonia on doctors

4.1.1 Information overload

During the "anti-epidemic" period at home, the general public, especially young doctors, are very concerned about the immediate changes of the epidemic, and have been surrounded by massive amounts of information about the epidemic for a long time. The overlapping of various epidemic information puts our emotional and psychological state in a highly stressed state, which in turn leads people into a negative psychological state. A large amount of epidemic-related information is usually several or even dozens of analytical angles and objective versions of an objective event. The vast number of young people represented by doctors have a certain ability to judge, but the multi-perspective contained in the massive fragmented information keeps doctors in the process of subjective strengthening such as right and wrong. Although this process strengthens self-awareness, Unable to achieve the growth of personal thoughts. A large amount of fragmented information is difficult to complete the integration of the ideological system without guidance. Once the doctor misses the opportunity to achieve ideological growth during school, if he cannot achieve further learning in the subsequent work, his judgment will be significantly lower., Unable to face the situation of work and life positively [14].

4.1.2 Psychological stress trauma

Every disaster will cause psychological problems to those who have experienced it. Within one year after the Wenchuan earthquake in 2008, more than 2100 psychological rescuers carried out more than 2,607,230 individual psychological interventions to the disaster-stricken people in Sichuan, and achieved good rescue results. However, this epidemic is very different from the psychological stress trauma caused by other disasters such as earthquakes, fires, and air crashes. It is manifested in the uncertainty of the target to be rescued due to the uncertainty of the spread of the epidemic and the probability of infection. Because there is no effective treatment, the prognosis is not good, and this brings a large-scale panic [15]. The above-mentioned characteristics of the new crown pneumonia epidemic are very prominent, causing doctors to produce nervousness and psychological trauma. This sense of powerlessness and despair in the face of the virus will further penetrate into study and life, resulting in a negative psychological state of being tired of learning and even the world.

4.1.3 Decline in social trust

The eight doctors who were the first to issue a warning about the epidemic were admonished. Due to the unfortunate death of Dr. Li Wenliang, public opinion was pushed to the climax of national discussions. Doctors and nurses and Hubei people are not among the people, and they need to coordinate with the hospital dean and even report to the police to deal with hurting the feelings of the majority of medical staff. A series of incidents such as the beating of the doctor and the tearing of his protective clothing by the family members of the patient were reprinted and spread in large numbers. The occurrence of these incidents is extremely sensitive and improperly guided during a special period. This series of public health issues will trigger a crisis of trust among doctors in government information transparency and law enforcement capabilities [16].

4.1.4 Worries about going abroad for further study

With the advancement of science and technology, medical professional knowledge is updated every day. Researchers need to continue to learn and communicate to better serve the people's health. The new crown pneumonia epidemic has caused a number of medical exchange destination countries to temporarily cut off personnel exchanges, and opportunities for studying abroad, such as studying abroad, and exchanges, will face many uncertainties. Although it is easy to resume personnel exchanges, the prejudice that "COVID-19 originated from China" among the population is difficult to eliminate in a short time, causing doctors to face more uncertainties when going abroad for communication and study [17].

4.2 Strategies to eliminate the psychological impact of the epidemic on doctors

Traditional Chinese medicine professional schools can design courses and activities in a comprehensive and multi-level targeted way to guide the traumatic psychology after the epidemic through the combination of class and class. After class, organize a series of themed activities such as "people-oriented, life first", "most beautiful retrograde", "my anti-epidemic", etc. to commend the alumni of the school who have outstanding performance in fighting the epidemic. Classes give full play to the professional expertise of the teachers of various Chinese medicine majors, and integrate epidemic cases into the content of professional courses, which can not only teach the professional courses vividly, but also do a good job in ideological and political education. There are the following principles in curriculum design [18].

4.2.1 Demonstrate the sense of responsibility and mission of medical staff

As a medical staff, the mission is to protect the lives and health of the people, and the responsibility is to overcome illness. As future medical staff, doctors should always keep this mission in mind and be proud of being a doctor or nurse.

4.2.2 Emphasize the sense of national pride and honor brought about by overcoming the epidemic

There are many hypotheses on the Internet that discuss the outcome of the new crown pneumonia in other countries. It is based on the H1NI epidemic that occurred in the United States in 2009, the Ebola virus epidemic that occurred in Africa in 2014, and the forest fires that occurred in Australia in 2019. The situation is compared horizontally, and the government’s response speed and the damage to the people are observed. It can be concluded that without the leadership of the Communist Party, there will be no united Chinese people. Without the effective functioning of the Chinese government, there will be no overriding determination and determination to prevent proliferation. The conclusion of the action. Applying this part of the material to education and teaching will enhance doctors' sense of pride in the united people and efficient government [19].

4.2.3 Highlight the role played by Chinese medicine in fighting the epidemic

Starting from the pneumonia diagnosis and treatment plan issued by the Health Commission on January 23, 2020, to the trial version 4 of the sixth version of the diagnosis and treatment plan issued on February 19, the diagnostic criteria and treatment plans of Chinese medicine have been systematically added. Various provinces and cities also put forward their own special Chinese medicine diagnosis and treatment plans, and clearly require that patients with confirmed diagnosis must take Chinese medicine. A large number of cases of recovered patients have once again proved that Chinese medicine is a well-deserved national treasure, and it is the Dinghai Shenzhen needle that can relieve the people from hanging upside down at a critical moment. Doctors from colleges and universities of Chinese medicine, as practitioners in the field of Chinese medicine in the future, must have a sense of pride in using Chinese medicine to save lives and heal the wounded, and a sense of mission to defend the honor of Chinese medicine [20].

4.3 Methods of psychological reconstruction of doctors after the epidemic

4.3.1 Actively guide doctors to resolve negative emotions

The real-time dynamic information of the new crown pneumonia epidemic is related to life and health. For a long time to follow the epidemic information, whether it is moved by the sacrifice of front-line medical staff, or worried about the increasing number of confirmed diagnoses, or because of the Wuhan Red Cross Being angry in doing so will cause people to be in strong emotional fluctuations for a long time, which in turn triggers a lot of emotional accumulation. Doctors should be guided to look at news events dialectically, stand rationally from the perspective of observation, and firmly maintain a correct political stance. It is necessary to use behavioral psychology tools to make detailed analysis, and teach doctors how to deal with sudden disasters through positive psychological hints. Through mental adjustment, goal strengthening, habit reconstruction, etc., it helps everyone to resolve various negative emotions and return to a normal learning lifestyle [21].

  1. 1.

    Mental adjustment.

From the objective facts of national development and changes, manpower helps doctors adjust their mentality. The biggest psychological state brought to doctors by the epidemic is fear and negativity. The unbalanced psychology brought about by the epidemic can be guided from the perspective of history. From the disasters experienced in the past, such as the similar “SARS” epidemic this time, we use facts to show the rapid changes in China after the epidemic, and the medical environment As well as the maturity and improvement of public health conditions, doctors can feel the changes in a series of conditions in their surrounding environment, technology, and quality of life since 2003, and convey that disasters will only make the nation more united, the people more enterprising, and the country more advanced [22].

  1. 2.

    Target enhancement.

Use detailed data and transparent information to guide doctors to correctly face negative information and strengthen adherence to professional goals. Negative emotions caused by individual adverse events such as the patient's death, the doctor being beaten during the treatment, the nurse being unable to enter the community home from get off work, etc., may mislead some doctors to reconsider their own career goals and make inappropriate choices. All of the above incidents are negative information during the high fever period, but more complete information will be obtained through long-term observation. For example, the patient has unfortunately passed away and the doctor is beaten, and the beater has been transferred to the judicial authority for serious processing. During the treatment, the patient was bitten by the dementia doctor because the patient was in a state of delirium during this period and the doctor had also done adequate protection. This is an accident. Nurses cannot enter the community when they return home from get off work, and the community property has been dealt with in accordance with the law. This can alleviate doctors' concerns about the lack of protection of the medical and nursing community and their rights and interests may be trampled on, and strengthen their career choices and goals.

  1. 3.

    Habit reconstruction.

Rebuilding good behaviors and habits helps to develop an active learning life. After the learning and life of the new semester begins, set a reasonable schedule according to the school's own situation, require appropriate activities, arrange reasonable courses, and change the doctor as soon as possible. Formed from January 23 A large number of mobile phones, no outdoor activities, irregular work and rest time and other behavioral habits. 21 days can change a person's behavior and habits. From home isolation to the end of the epidemic, it has been more than 21 days. Rebuilding good behavior and habits requires school organization, teacher guidance, and classmates' influence to complete.

4.3.2 Well-designed professional courses combined with epidemic cases

  1. 1.

    Establish a case database of advanced deeds of medical staff.

Establish a case database of advanced deeds of medical staff in the new crown pneumonia epidemic, and improve professional classroom teaching materials. In the fight against the new crown pneumonia, many public incidents concerning medical staff have emerged. Establish and continuously improve the case database of medical staff's deeds during the new crown pneumonia epidemic, and track the results of the treatment, and organize follow-up measures such as timely corrections and remedies. Restore the objective facts of the incident to avoid misunderstandings caused by the fact that the news fades and doctors do not have complete information. Respond to hot events in an all-round way, and deliver progress information that reflects the overall cognition and processing capabilities of the society. By mastering a multi-angle observation perspective, the doctor is willing to accept a positive perspective to trigger discussions and stimulate their enthusiasm for learning.

  1. 2.

    Establish a case database of the deeds of pharmacy and basic medicine personnel.

Establish a case database of advanced deeds of pharmacy and basic medical personnel in the new crown pneumonia epidemic, and improve professional classroom teaching materials. During the development of this epidemic, medical staff are fighting ahead and the prerequisite for decisive progress is progress in basic research and treatment of viruses and diseases. The isolation of virus strains, the prediction of virus infectivity, the formulation of prevention and control measures, the development of inspection methods, the determination of medication rules, the differentiation of Chinese medicine, etc., every step of the development is inseparable from the day and night scientific research by pharmacy and basic medicine practitioners.. Although the pharmacy and basic medical researchers are behind, they also play a vital role in winning this anti-virus battle. Establishing a teaching case database of the achievements made by medical researchers during the epidemic and the incidents of the team behind them can lead doctors to learn about pharmacy and basic medicine in the context of fighting the epidemic.

  1. 3.

    The matching of specific cases and TCM professional knowledge forms a vivid medical professional course.

The case teaching model is very vivid, allowing doctors to experience knowledge in cases, which is of great help to theoretical subjects. In the process of professional curriculum design, it is necessary to find the related stories of professional knowledge from the case library, and integrate the content of professional courses into the stories. Using cases familiar to doctors can make doctors have an "empathy effect" and have a strong psychological impact on them. The designed epidemic case teaching should enable doctors to experience the honor of applying theoretical knowledge to solve major medical problems in practical work, and inspire enthusiasm for learning and better master professional knowledge.

5 Conclusion

The Chinese nation has experienced countless plague tests in its long history, and each time it has overcome the epidemic with the wisdom and unity of the people and extensive and profound Chinese medicine. It is difficult to rejuvenate a country, and every tribulation will push the level of civilization and social development of the Chinese nation to a new level. As a professional teacher of Chinese medicine colleges, we must not only impart solid professional knowledge to doctors, but also pass on to doctors the strong national belief of the Chinese nation of indomitable, courageous to fight, and who will win the battle. In the current and future teaching process, we must also be good at grasping the changes in the doctor's psychological state and guiding the doctor to restore a positive and optimistic state of study, work and life. Cloud data will dominate the future of the database market. More and more databases will be deployed or migrated to cloud platforms. This is an inevitable result of technological development and cost considerations. Small and medium-sized enterprises may choose public cloud databases because of cost considerations. For large companies or enterprises and institutions, considering data security issues, they will build their own private cloud databases. In the current private cloud environment, there are few cloud database service system solutions, and enterprises have a strong demand for cloud databases. Based on the laboratory private cloud platform, this paper studies the automated deployment framework and proposes cloud database services under the private cloud platform. It also designed and implemented a cloud database service system. This article also proposes a static deployment solution for mysql database service, studies the open source automated deployment framework, compares the advantages and disadvantages of SlatStack and Ansible automated deployment tools, provides strong support for the automated deployment of cloud databases, compares static deployment and The advantages and disadvantages of dynamic deployment, a static deployment plan for mysql database is proposed. This paper first divides the limited character input UDRN into multiple clusters through the K-means algorithm, and then uses the golden section method to obtain the optimal amount of power purchased by the user from the relay to maximize the utility function of the user node. Then, the mutual preference matrix between the user and the relay is established, and a utility-based stable matching algorithm for the limited character input EH relay network is proposed, which aims to derive the sub-optimal utility optimization scheme of the network. Finally, analyze the algorithm's implementation, convergence, complexity and communication overhead.