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Testing the 5GMETA Platform

Introduction

This document describes some Python scrips to test the 5GMETA Platform. The test are in the folder ./tests.

Pre-requisities

  • Create a Python virtuel env
  • Install the requirements python-qpid-proton - including any of its dependencies
  • Linux distribution
  • Python version 3.5+
  • (you have to modify address.py in order to put the appropriate ip, port and topic given by your message broker)

Sample Datasets to test a CAM application

The table lists the datasets which can be used during the development of a CAM application.

5GMETA DATA TYPE DESCRIPTION TILE SAMPLE ReadMe
C-ITS Simulation Cooperative Awareness Messages (position, heading, speed, acceleration, etc...) from simulated vehicles anywhere/worldwide WebApp UI README
C-ITS Position, heading, speed and acceleration from vehicles in Donostia (Spain) 0313331232 cits-vicomtech-donostia.json README
C-ITS Position, heading, speed and acceleration from vehicles in Toulouse (France) 120222021 cits-vicomtech-toulouse.json README
C-ITS Category, Position, orientation, speed and cam_id, object_id from vehicles, person, bycicle..etc in MODENA (Italy) 1202231113220102 cits-unimore-modena-masa.json README
C-ITS Camera_id, space_id ,space position, Occupied Or Empty, from Parking Lots in MODENA (Italy) 1202231113220102 cits-unimore-modena-pld.json README
C-ITS GPS Position, dms_level, dms_trigger from Driver monitoring system in MODENA (Italy) 1202231113220102 cits-unimore-modena-dms.json README
C-ITS Position, heading, speed and acceleration from vehicles in MODENA (Italy) 1202231113220102 cits-unimore-modena-cam.json README
image jpg from Donostia (Spain) 0313331232 image-sample-vicomtech-donostia.jpg README
image jpg from Toulouse (France) 120222021 image-sample-vicomtech-toulouse.jpg README
C-ITS Position, heading, speed and acceleration from vehicles in Versailles (France) 1202200101311 cits-versailles_area-cam.json README
C-ITS Status of traffic light in Versailles (France) 1202200101311 cits-versailles_area-spat.json README
C-ITS Parking area occupancy in Versailles (France) 1202200101311 cits-versailles_area-pam.json README
C-ITS Traffic counting from with 2 metric (Throughput, Occupation rate) with 5 sensors in Versailles (France) 1202200101311 traffic_sensors_samples.json README

Image Sender

The examples can be found in the folder ./tests/examples/message-data-broker/image_sender_python.

Similarly to the C-ITS sender example, you need to configure the address of the data broker.

Then, in one terminal window run:

python3 sender.py

For S&D connected to a database, the images to be send are stored in sample_images folder. The messages being sent by the sender can be consummed by typing:

python3 receiver.py

Debegging using ActiveMQ Web Console

The ActiveMQ admin Web Console can be used to check Messages Enqueued / Dequeued counts match.

You can control which AMQP server the examples try to connect to and the messages they send by changing the values in config.py

You have to take into account that any modification made on dataflowmetadata must be applied too into the content.py file in order to generate the appropriate content.

C-ITS Data Sender

The examples can be found in the folder ./tests/examples/message-data-broker/cits_sender_python.

  • Modify address.py to put the appropriate ip, port and topic given by your message broker or run with options:

  • Additional arguments as highlighted below could be parsed to the sender.py :

- h, --help            show this help message and exit
- a ADDRESS, --address=ADDRESS
= address to which messages are sent (default )
- m MESSAGES, --messages=MESSAGES
= number of messages to send (default 100)
- t TIMEINTERVAL, --timeinterval=TIMEINTERVAL
= messages are sent continuosly every time interval seconds (0: send once) (default 10)
  • In one terminal window run wither of the sender scripts depending upon whether you are running your S&D connected to an database or not. You can add additional arguments as shown before:
python3 sender.py

Or test by:

python3 sender_with_sd_database_support.py

Example output can be seen below:

Sender example

To debug and check if messages are being sent, run in another terminal to receive messages:

Run to see the received messages on the subscribed AMQP topic.

python3 receiver.py

Receiver example

  • Use the ActiveMQ admin web page to check Messages Enqueued / Dequeued counts match.

  • You can control which AMQP server the examples try to connect to and the messages they send by changing the values in config.py

  • NB: You have to take into account that any modification made on dataflowmetadata must be applied too into the content.py file in order to generate the appropriate content.

Pseudo movement example

This example demonstrates data being produced by a moving sensor device.

  • Added some movement around a fixed GPS position in order to simulate movement. Example: - [cits_send_moving_location.py]

This way we can move around a MEC that covers tiles:

  • 031333123201033
  • 031333123201211

and a secondary one that covers tiles:

  • 031333123201212
  • 031333123201213
  • 031333123201223
  • 031333123202223

End-to-End Data Production and Consuption Examples

Description

As introduced in the previous section, provides examples how to produce (cits/image) data from a Sensor&Device to the MEC using Python AMQP reactor API with ActiveMQ.

In this section, we will explain in further detail how to implement a data producer. Specific examples will then be provided in the following pages of this documentation.

Refering the examples presented, following are some essential parameters while producing data on the 5GMETA platform:

  • source_id: a Unique Identifier to distinguish the source of generated data.
  • tile: Tile of the source from where the data is being generated in form of QuadKey code. e.g. 1230123012301230 (must be 18 chars in [0-3])
  • datatype: should be one of the allowed datatype [cits, video, image]
  • sub_datatype: depends upon on the datatype e.g. cam, denm, mappem

Generic producer structure

A typical producer will contain the following fields, as it can be seen in the examples:

  • Discovery Registration API : This API helps you connect your S&Ds and push data to the MEC within a specified tile.

  • Getting tile of the source from its current GPS position:

tileTmp = Tile.for_latitude_longitude(latitude=latitude, longitude=longitude, zoom=18)
  • Getting the message-broker access from the MEC within the previous tile:
service="message-broker"

messageBroker_ip, messageBroker_port = discovery_registration.discover_sb_service(tile,service)
  • Getting AMQP Topic and dataFlowId to push data into the Message Broker:
dataflowId, topic = discovery_registration.register(dataflowmetadata,tile)

opts.address="amqp://"+username+":"+password+"@"+messageBroker_ip+":"+str(messageBroker_port)+":/topic://"+topic

jargs = json.dumps(args)

Usage

Let's take an example of CITS message producer as shown here in sender.py for reference.

  • Pass the latitude and longitude GPS position of your sensor device as shown here in :
# Geoposition - Next steps: from GPS device.
latitude = 43.3128
longitude = -1.9750
  • Replace with your metadata in this section shown below.
dataflowmetadata = {
    "dataTypeInfo": {
        "dataType": "cits",
        "dataSubType": "json"
    },
    "dataInfo": {
        "dataFormat": "asn1_jer",
        "dataSampleRate": 0.0,
        "dataflowDirection": "upload",
        "extraAttributes": None,
    },
    "licenseInfo": {
        "licenseGeolimit": "europe",
        "licenseType": "profit"
    },
    "dataSourceInfo": {
        "sourceTimezone": 2,
        "sourceStratumLevel": 3,
        "sourceId": 1,
        "sourceType": "vehicle",
        "sourceLocationInfo": {
            "locationQuadkey": tile,
            "locationCountry": "ESP",
            "locationLatitude": latitude,
            "locationLongitude": longitude
        }
    }
}
  • Use the sample content.py to generate your messages. Here as you can see the *msgbody contains the CITS message.
def messages_generator(num, tile, msgbody='body_cits_message'):
    messages.clear()

    #print("Sender prepare the messages... ")
    for i in range(num):
        props = {
                    "dataType": "cits",
                    "dataSubType": "cam",
                    "dataFormat":"asn1_jer",
                    "sourceId": 1,
                    "locationQuadkey": tile+str(i%4),
                    "body_size": str(sys.getsizeof(msgbody))
                    }

        messages.append( Message(body=msgbody, properties=props) )

Credits

TODO: Add the credits

Conclusion

TODO: Add the conclusion

References