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Device Control

Similar to data collection, after setting up the commands for the device in deviceshifu_configmap.yaml, we can communicate with deviceshifu via HTTP/gRPC, and deviceshifu will convert the commands we send into the form of the protocol supported by the device and send them to the device. After the device receives the command, it can perform the corresponding operation to control the device.

Automated Device Control with Data Collection

  1. Here, we create another virtual device PLC (if you have not tried the PLC device, you can click to view).

    $ kubectl get pods -n deviceshifu
    deviceshifu-opcua-deployment-765b77cfcf-dnhjh 1/1 Running 0 14m
    deviceshifu-plc-deployment-7f96585f7c-6t48g 1/1 Running 0 7m8s

    At this point we have started two deviceshifu which have each established a connection to a device. We can link the two deviceshifu, that is, when the thermometer temperature exceeds the threshold, set the lowest position of Q area of PLC to 1, and set it back to 0 when the thermometer temperature is below the threshold.

  2. Write the program related to the control device.

    package main  

    import (

    func main() {
    targetUrl := "http://deviceshifu-thermometer.deviceshifu.svc.cluster.local/read_value"
    req, _ := http.NewRequest("GET", targetUrl, nil)
    var isHigh bool
    for {
    res, _ := http.DefaultClient.Do(req)
    Body, _ := ioutil.ReadAll(res.)
    temperature, _ := strconv.Atoi(string(body))
    if temperature > 20 && isHigh == false {
    isHigh = true
    } else if temperature <= 20 && isHigh == true {
    isHigh = false
    log.Printf("Now remperature is: %d", temperature)
    Time.Sleep(5 * time.Second)
    Sleep(5 * time.Second) }

    func setPLCBit(value string) {
    targetUrl := "http://deviceshifu-plc/sendsinglebit?rootaddress=Q&address=0&start=0&digit=0&value=" + value
    req, _ := http.NewRequest("GET", targetUrl, nil)
    res, _ := http.DefaultClient.Do(req)
    defer res.Body.Close()
  3. For the above program, we can package it as a docker image and load it into the cluster so that it can better communicate with deviceshifu. Create the following Dockerfile file.

    # syntax=docker/dockerfile:1  
    FROM golang:1.17-alpine
    WORKDIR /app
    COPY go.mod . /
    RUN go mod download
    COPY *.go . /RUN
    RUN go build -o /high-temperature-control-plc
    EXPOSE 11111
    CMD [ "/high-temperature-control-plc" ]
  4. Generate a docker image using the Dockerfile file.

    docker build --tag high-temperature-control-plc:v0.0.1
  5. After that we load the docker image into the cluster.

    kind load docker-image high-temperature-control-plc:v0.0.1
  6. Run the data acquisition program we wrote.

    kubectl run high-temperature-control-plc --image=high-temperature-control-plc:v0.0.1
  7. Also, in order for us to see the values of the PLC device, we load another nginx image.

    kubectl run nginx --image=nginx:1.21 -n deviceshifu
  8. At this point we have the following pods, all in the Running state.

    $ kubectl get pods -n deviceshifu
    deviceshifu-plc-deployment-7f96585f7c-87zb4 1/1 Running 0 20m
    deviceshifu-thermometer-deployment-7b69b89b88-crwzx 1/1 Running 0 67m
    high-temperature-control-plc 1/1 Running 0 8m54s
    nginx 1/1 Running 0 61m
  9. The automation device control program we wrote is running, and you can view the data obtained by the program by viewing the live log.

    $ kubectl logs high-temperature-control-plc -n deviceshifu -f 
    2022/07/07 03:05:07 Now remperature is: 29
    2022/07/07 03:05:12 Now remperature is: 10
    2022/07/07 03:05:17 Now remperature is: 23
    2022/07/07 03:05:22 Now remperature is: 30

    Sleep(5 * time.Second)in the program to make it easier to observe the data (to improve the acquisition accuracy, you can turn it down to increase the acquisition frequency). At this point we enter another command into thenginx` container.

    kubectl exec -it nginx -n deviceshifu -- bash
  10. When the program gets a temperature above the threshold we get the PLC value via curl.

    $ curl "http://deviceshifu-plc/getcontent?rootaddress=Q&address=0&start=0"; echo
  11. When the program gets a temperature below the threshold we get the PLC value again via curl.

    $ curl "http://deviceshifu-plc/getcontent?rootaddress=Q&address=0&start=0"; echo

By now, we have achieved automated control of the PLC device by collecting real-time data from the virtual thermometer.