This document's goal is to show how to develop a new IoT Agent step by step. To do so, a simple invented HTTP protocol
will be used, so it can be tested with simple command line instructions as curl
and nc
.
The invented protocol will be freely adapted from Ultralight 2.0. Whenever a device wants to send an update, it will send a request as the following:
curl -X GET 'http://127.0.0.1:8080/iot/d?i=ULSensor&k=abc&d=t|15,l|19.6' -i
Where:
- i: is the device ID.
- k: the API Key for the device's service.
- d: the data payload, consisting of key/value pairs separated by a pipe ('|'), with each pair separated by comma (',');
This tutorial expects a Node.js v0.10 (at least) installed and working on your machine. It also expects you to have access to a Context Broker (without any security proxies).
In this first chapter, we will just develop an IoT Agent with a fully connected North Port. This will send and receive NSGI traffic and can be administered using the IoT Agent's Device Provisioning API. The South Port will remain unconnected and no native protocol traffic will be sent to the devices. This may seem useless (and indeed it is) but it will serve us well on showing the basic steps in the creation of an IoT Agent.
First of all, we have to create the Node project. Create a folder to hold your project and type the following instruction:
npm init
This will create the package.json
file for our project. Now, add the following lines to your project file:
"dependencies": {
"iotagent-node-lib": "*"
},
And install the dependencies, executing, as usual:
npm install
The first step is to write a configuration file, that will be used to tune the behavior of our IOTA. The contents
can be copied from the config-basic-example.js
file, in this same folder. Create a config.js
file with it
in the root folder of your project. Remember to change the Context Broker IP to your local Context Broker.
Now we can begin with the code of our IoT Agent. The very minimum code we need to start an IoT Agent is the following:
var iotAgentLib = require('iotagent-node-lib'),
config = require('./config');
iotAgentLib.activate(config, function(error) {
if (error) {
console.log('There was an error activating the IOTA');
process.exit(1);
}
});
The IoT Agent is now ready to be used. Execute it with the following command:
node index.js
The North Port interface should now be fully functional, i.e.: management of device registrations and configurations.
In the previous section we created an IoT Agent that exposed just the North Port interface, but that was pretty useless (aside from its didactic use). In this section we are going to create a simple South Port interface. It's important to remark that the nature of the traffic South of the IoT Agent itself has nothing to do with the creation process of an IoT Agent. Each device protocol will use its own mechanisms and it is up to the IoT Agent developer to find any libraries that would help him in its development. In this example, we will use Express as such library.
In order to add the Express dependency to your project, add the following line to the dependencies
section of the
package.json
:
"express": "*",
The require section would end up like this (the standard http
module is also needed):
var iotAgentLib = require('iotagent-node-lib'),
http = require('http'),
express = require('express'),
config = require('./config');
And install the dependencies as usual with npm install
. You will have to require both express
and http
in
your code as well.
Now, in order to accept connections in our code, we have to start express first. With this purpose in mind, we will
create a new function initSouthbound()
, that will be called from the initialization code of our IoT Agent:
function initSouthbound(callback) {
southboundServer = {
server: null,
app: express(),
router: express.Router()
};
southboundServer.app.set('port', 8080);
southboundServer.app.set('host', '0.0.0.0');
southboundServer.router.get('/iot/d', manageULRequest);
southboundServer.server = http.createServer(southboundServer.app);
southboundServer.app.use('/', southboundServer.router);
southboundServer.server.listen(southboundServer.app.get('port'), southboundServer.app.get('host'), callback);
}
This Express code sets up a HTTP server, listening in the 8080 port, that will handle incoming requests targeting
path /iot/d
using the middleware manageULRequest()
. This middleware will contain all the logic south of the
IoT Agent, and the library methods we need in order to progress the information to the Context Broker. The code
of this middleware would be as follows:
function manageULRequest(req, res, next) {
var values;
iotAgentLib.retrieveDevice(req.query.i, req.query.k, function(error, device) {
if (error) {
res.status(404).send({
message: 'Couldn\'t find the device: ' + JSON.stringify(error)
});
} else {
values = parseUl(req.query.d, device);
iotAgentLib.update(device.name, device.type, '', values, device, function(error) {
if (error) {
res.status(500).send({
message: 'Error updating the device'
});
} else {
res.status(200).send({
message: 'Device successfully updated'
});
}
});
}
});
}
For this middleware we have made use of a function parseUl()
that parses the data payload and transforms it
in the data object expected by the update function (i.e.: an attribute array with NGSI syntax):
function parseUl(data, device) {
function findType(name) {
for (var i=0; i < device.active.length; i++) {
if (device.active[i].name === name) {
return device.active[i].type;
}
}
return null;
}
function createAttribute(element) {
var pair = element.split('|'),
attribute = {
name: pair[0],
value: pair[1],
type: findType(pair[0])
};
return attribute;
}
return data.split(",").map(createAttribute);
}
Here as an example of the output of the function return for the UL payload t|15,l|19.6
:
[
{
"name": "t",
"type": "celsius",
"value": "15"
},
{
"name": "l",
"type": "meters",
"value": "19.6"
}
]
The last thing to do is to invoke the initialization function inside the IoT Agent startup function. The next excerpt
show the modifications in the activate()
function:
iotAgentLib.activate(config, function(error) {
if (error) {
console.log('There was an error activating the IOTA');
process.exit(1);
} else {
initSouthbound(function (error) {
if (error) {
console.log('Could not initialize South bound API due to the following error: %s', error);
} else {
console.log('Both APIs started successfully');
}
});
}
});
Some logs were added in this piece of code to help debugging.
Once the IOTA is finished the last thing to do is to test it. To do so, launch the IoT Agent and provision a new device
(an example for provisioning can be found in the examples/howtoProvisioning1.json
file). Once the device is
provisioned, send a new measure by using the example command:
curl -X GET 'http://127.0.0.1:8080/iot/d?i=ULSensor&k=abc&d=t|15,l|19.6' -i
Now you should be able to see the measures in the Context Broker entity of the device.
The IoT Agents also give the possibility for the device to be asked about the value of one of its measures, instead of
reporting it. In order to do so, the device must be capable of receiving messages of some kind. In this case, we are
going to simulate an HTTP server with nc
in order to see the values sent by the IOTA. We also have to decide a syntax
for the protocol request for asking the device about a measure. For clarity, we will use the same HTTP GET request we
used to report a measure, but indicating the attribute to ask instead of the data payload. Something like:
curl -X GET 'http://127.0.0.1:9999/iot/d?i=ULSensor&k=abc&q=t,l' -i
In a real implementation, the server will need to know the URL and port where the devices are listening, in order to send the request to the appropriate device. For this example, we will assume that the device is listening in port 9999 in localhost. For more complex cases, the mechanism to bind devices to addresses would be IoT-Agent-specific (e.g.: the OMA Lightweight M2M IoT Agent captures the address of the device in the device registration, and stores the device-specific information in a MongoDB document).
Being lazy attributes of a read/write nature, another syntax has to be declared for updating. This syntax will mimic the one used for updating the server:
curl -X GET 'http://127.0.0.1:9999/iot/d?i=ULSensor&k=abc&d=t|15,l|19.6' -i
Both types of calls to the device will be distinguished by the presence or absence of the d
and q
attributes.
A HTTP request library will be needed in order to make those calls. To this extent, mikeal/request
library will be used.
In order to do so, add the following require statement to the initialiation code:
request = require('request');
and add the request
dependency to the package.json
file:
"dependencies": [
[...]
"request": "*",
]
The require section should now look like this:
var iotAgentLib = require('iotagent-node-lib'),
http = require('http'),
express = require('express'),
request = require('request'),
config = require('./config');
The main step to complete in order to implement the Lazy attributes mechanism in the IoT Agent is to provide handlers for the context
provisioning requests. At this point, we should provide two handlers: the updateContext
and the queryContext
handlers.
To do so, we must first define the handlers themselves:
function queryContextHandler(id, type, service, subservice, attributes, callback) {
var options = {
url: 'http://127.0.0.1:9999/iot/d',
method: 'GET',
qs: {
q: attributes.join()
}
};
request(options, function (error, response, body) {
if (error) {
callback(error);
} else {
callback(null, createResponse(id, type, attributes, body));
}
});
}
The queryContext
handler is called whenever a queryContext
request arrives at the North port of the IoT Agent. It is invoked once
for each entity requested, passing the entity ID and Type as the parameters, as well as a list of the attributes that are
requested. In our case, the handler uses this parameters to compose a request to the device. Once the results of the device
are returned, the values are returned to the caller, in the NGSI attribute format.
In order to format the response from the device in a readable way, we created a createResponse()
function that maps
the values to its correspondent attributes. This function assumes the type of all the attributes is "string" (this will
not be the case in a real scenario, where the IoT Agent should retrieve the associated device to guess the type of its
attributes). Here is the code for the createResponse()
function:
function createResponse(id, type, attributes, body) {
var values = body.split(','),
responses = [];
for (var i = 0; i < attributes.length; i++) {
responses.push({
name: attributes[i],
type: "string",
value: values[i]
});
}
return {
id: id,
type: type,
attributes: responses
};
}
function updateContextHandler(id, type, service, subservice, attributes, callback) {
var options = {
url: 'http://127.0.0.1:9999/iot/d',
method: 'GET',
qs: {
d: createQueryFromAttributes(attributes)
}
};
request(options, function (error, response, body) {
if (error) {
callback(error);
} else {
callback(null, {
id: id,
type: type,
attributes: attributes
});
}
});
}
The updateContext handler deals with the modification requests that arrive at the North Port of the IoT Agent. It is invoked once for each entity requested (note that a single request can contain multiple entity updates), with the same parameters used in the queryContext handler. The only difference is the value of the attributes array, now containing a list of attribute objects, each containing name, type and value. The handler must also make use of the callback to return a list of updated attributes.
For this handler we have used a helper function called createQueryFromAttributes()
, that transforms the NGSI representation
of the attributes to the UL type expected by the device:
function createQueryFromAttributes(attributes) {
var query = "";
for (var i in attributes) {
query += attributes[i].name + '|' + attributes[i].value;
if (i != attributes.length -1) {
query += ',';
}
}
return query;
}
Once both handlers have been defined, they have to be registered in the IoT Agent, adding the following code to the setup function:
iotAgentLib.setDataUpdateHandler(updateContextHandler);
iotAgentLib.setDataQueryHandler(queryContextHandler);
In order to test it, we need to create an HTTP server simulating the device. The quickest way to do that may be using netcat. In order to start it just run the following command from the command line (Linux and Mac only):
nc -l 9999
This will open a simple TCP server listening on port 9999
, where the requests from the IoT Agent will be printed. In order for
the complete workflow to work (and to receive the response in the application side), the HTTP response has to be written
in the nc
console (although for testing purposes this is not needed).
While netcat is great to test simple connectivity, you will need something just a bit more complex to get the complete
scenario working (at least without the need to be incredibly fast sending your response). In order to do so, a simple
echo server was created, that ansers 42 to any query to its /iot/d
path. You can use it to test your attributes one by
one (or you can modify it to accept more requests and give more complex responses). Copy the Echo Server script
to the same folder of your IoTAgent (as it uses the same dependencies). In order to run the echo server, just
execute the following command:
node echo.js
Once the mock server has been started (either nc
or the echo
server), proceed with the following steps to test your implementation:
- Provision a device with two lazy attributes. The following request can be used as an example:
POST /iot/devices HTTP/1.1
Host: localhost:4041
Content-Type: application/json
fiware-service: howtoserv
fiware-servicepath: /test
Cache-Control: no-cache
Postman-Token: 993ac66b-72da-9e96-ab46-779677a5896a
{
"devices": [
{
"device_id": "ULSensor",
"entity_name": "Sensor01",
"entity_type": "BasicULSensor",
"lazy": [
{
"name": "t",
"type": "celsius"
},
{
"name": "l",
"type": "meters"
}
],
"attributes": [
]
}
]
}
- Execute a queryContext or updateContext against one of the entity attributes (use a NGSI client of curl command).
POST /v1/queryContext HTTP/1.1
Host: localhost:1026
Content-Type: application/json
Accept: application/json
Fiware-Service: howtoserv
Fiware-ServicePath: /test
Cache-Control: no-cache
Postman-Token: 1dc568a1-5588-059c-fa9b-ff217a7d7aa2
{
"entities": [
{
"isPattern": "true",
"id": ".*",
"type": "BasicULSensor"
}
],
"attributes" : [
"l"]
}
-
Check the received request in the nc console is the expected one.
-
(In case you use netcat). Answer the request with an appropriate HTTP response and check the result of the
queryContext
orupdateContext
request is the expected one. An example of HTTP response, for a query to thet
andl
attributes would be:
HTTP/1.0 200 OK
Content-Type: text/plain
Content-Length: 3
5,6
This same response can be used both for updates and queries for testing purposes (even though in the former the body won't be read).
For some IoT Agents, it will be useful to know what devices or configurations were registered in the Agent, or to do some actions whenever a new device is registered. All this configuration and provisioning actions can be performed using two mechanisms: the provisioning handlers and the provisioning API.
The handlers provide a way for the IoT Agent to act whenever a new device, or configuration is provisioned. This can be used for registering the device in external services, for storing important information about the device, or to listen in new ports in the case of new configuration. For the simple example we are developing, we will just print the information we are receiving whenever a new device or configuration is provisioned.
We need to complete two steps to have a working set of provisioning handlers. First of all, defining the handlers themselves. Here we can see the definition of the configuration handler:
function configurationHandler(configuration, callback) {
console.log('\n\n* REGISTERING A NEW CONFIGURATION:\n%s\n\n', JSON.stringify(configuration, null, 4));
callback(null, configuration);
}
As we can see, the handlers receive the device or configuration that is being provisioned, as well as a callback. The handler MUST call the callback once in order for the IOTA to work properly. If an error is passed as a parameter to the callback, the provisioning will be aborted. If no error is passed, the provisioning process will continue. This mechanism can be used to implement security mechanisms or to filter the provisioning of devices to the IoT Agent.
Note also that the same device
or configuration
object is passed along to the callback. This lets the IoT Agent change some
of the values provisioned by the user, to add or restrict information in the provisioning. To test this feature, let's
use the provisioning handler to change the value of the type of the provisioning device to CertifiedType
(reflecting
some validation process performed on the provisioning):
function provisioningHandler(device, callback) {
console.log('\n\n* REGISTERING A NEW DEVICE:\n%s\n\n', JSON.stringify(device, null, 4));
device.type = 'CertifiedType';
callback(null, device);
}
Once the handlers are defined, the new set of handlers has to be registered into the IoT Agent:
iotAgentLib.setConfigurationHandler(configurationHandler);
iotAgentLib.setProvisioningHandler(provisioningHandler);
Now we can test our implementation by sending provisioning requests to the North Port of the IoT Agent. If we provision a new device
into the platform, and then we ask for the list of provisioned devices, we shall see the type of the provisioned device
has changed to CertifiedType
.