APIs for IOT and FOG computing

Rajnish Kumar
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Rajnish Kumar

Enabling APIs, IOT (Internet Of Things), Artificial Intelligence ecosystem to our customer and latest technology trend. Worked with our client over 20 years in Project Management, Architecture of Enterprise application and application development .
Extensively worked on IOT, Microservices, APIs,SOA application, Cloud, Amazon AWS,Big Data, Analytics, Artificial intelligence and Security.
Rajnish Kumar
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Latest posts by Rajnish Kumar (see all)

IOT (Internet Of Things) is transforming whole business and bringing new revolution in all kinds of business. These IOT devices generating terabytes of data. To handle unprecedented volume, variety and velocity of data, IOT needs new kind of infrastructure to support whole IOT eco system. FOG computing is a part of IOT eco system to support large volume of data with quick response. I explained in my previous blog, how FOG computing is now becoming major role in IOT devices. FOG is intermediate platform to collaborate between Cloud computing and Edge computing(IOT) to transfer data. Fog can hold small number of data and less computing power. Large data is stored in cloud and heavy computing is done in Cloud.

API (Application Programming Interface) have major role to transfer data from edge device (IOT) to Fog node and from fog node to Cloud (Internet). API is helping to collaborate between edge device to Fog node and Fog node to Cloud. API is playing major role to maintain volume, variety and velocity of data in IOT infrastructure.

API works on HTTP/HTTPS protocol. APIs are light weight and simple. Enabling APIs take very small amount of resource. So, API can enable in small system and consume without losing too much resources.  This API property helps to transfer data from Edge device(IOT) to Fog node and from Fog node to Cloud. API is not part of mechanical role. API is responsible for the optimization of data transfer. Proper enabling of APIs between these nodes increase the efficiency and computational power to all IOT devices. Fog node is intermediate node between IOT device and cloud. So, Fog node will be responsible to receive data from edge(IOT) device and transfer these data to Cloud. Communication between Edge(IOT) device to Fog node is very frequent. Data provided by API is responsible for all intermediate and quick computation on FOG node.

Cloud is still big stake holder for holding all data and large computation from IOT device.  API is providing data to cloud from FOG node in certain interval for heavy computation. As Edge(IOT) system getting more complex Fog computation responsibility will increase and API will come on picture to provide more data to Fog and from fog node to cloud.

API Integration of IOT with Fog and Cloud computing.

These are few benefits by enabling APIs for IOT devices and Fog Nodes

  • API provides flexibility to connect any IOT device to FOG node and FOG node to cloud network.
  • API provides seamless connectivity between these systems.
  • API brings whole IOT system in one seamless environment So, it is very easy to debug these systems.
  • API is very easy to develop and deploy so it’s easy to maintain these systems.
  • Provisioning of IOT device has also become very easy by enabling API.
  • According to Gartner study, Security of IOT is one of big concern. API provides whole one seamless system and network to mitigate this risk.

Fog Computing and Edge computing

Rajnish Kumar
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Rajnish Kumar

Enabling APIs, IOT (Internet Of Things), Artificial Intelligence ecosystem to our customer and latest technology trend. Worked with our client over 20 years in Project Management, Architecture of Enterprise application and application development .
Extensively worked on IOT, Microservices, APIs,SOA application, Cloud, Amazon AWS,Big Data, Analytics, Artificial intelligence and Security.
Rajnish Kumar
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Latest posts by Rajnish Kumar (see all)

IOT, Connect car, Automated car getting lot of traction in current word. All big companies want to be part of this process. All kind of sensors are installed in these vehicles. These sensors generate Terabytes of data and computing these data to run vehicle smoothly. Connected car or IOT based devices are completely based on computing power and quick response.

Sending data and computing these data in cloud could be catastrophic. Any network latency and processing delay might end with bad result. For example, your automated car is traversing through busy street. Suddenly a person comes in front of automated car. In this scenario, any network latency, slowness of computation and analysis effects the decision and subsequent action (Apply brake on car).

In IOT based device, any computing near to IOT device can reduce this risk. So how can we make this happen, if your all computing power are in cloud and data is in cloud.

Fog Computing & Edge computing

FOG Computing–In context of IOT, if intelligence pushes d down to the local area network (LAN) and compute these data in IOT gateway or FOG node will reduce network latency risk. Fogging or FogNetwork is decentralized computing and stores data in most logical and efficient place between IOT device and the cloud.

In FOG computing, data transported from IOT to Cloud need many steps.

  1. Signals from IOT is transported through wire to I/O point of device programmable automation controller(PLC). PLC execute control system program to automate system.
  2. Control system program sends data to protocol gateway, which convert this data into a protocol, understand internet systems such as MQTT or HTTP.
  3. At the end, data is send to fog node or IOT gateway on the LAN, which collects the data and preform analysis and computing on data. This even stores the data to transfer further to cloud network for later processing and intelligence.

Edge Computing — Edge computing refers to any computing infrastructure near to source of data (i.e. IOT device). So, Making IOT device smart and intelligent enough to take decision near to data gateway. The role of edge computing is to process data, store data in local device and transfer data to fog or cloud network. Above all processes are automated through PAC (Programmable automation controller) by executing board controlled system program. In edge computing, intelligence literally push to edge of network where our IOT device and outside network first connect to each other.

Mulesoft: Twilio API Integration

Rajnish Kumar
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Rajnish Kumar

Enabling APIs, IOT (Internet Of Things), Artificial Intelligence ecosystem to our customer and latest technology trend. Worked with our client over 20 years in Project Management, Architecture of Enterprise application and application development .
Extensively worked on IOT, Microservices, APIs,SOA application, Cloud, Amazon AWS,Big Data, Analytics, Artificial intelligence and Security.
Rajnish Kumar
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mulesoft-logoplustwilio

Twilio is a cloud based communication company that enables users to use standard web languages to build voice, VoIP, and SMS apps via a web API. Twilio provides a simple hosted API and markup language for businesses to quickly build scalable, reliable and advanced voice and SMS communications applications. Twilio based telephony infrastructure enable web programmer to integrate real time phone call, SMS or VOIP to their application.

Mulesoft provides cloud connector to integrate Twilio Api within Mulesoft. Mulesoft Cloud connector provides a simple and easy way to integrate with these Twilio APIs, and then use them as services within Mulesoft. Mulesoft-Twilio connector provides a platform for developer to develop and integrate their application easily and quickly with Twilio.

Before start integration of Mulesoft with Twilio, create your Twilio account and get “ACCOUNT SID” and “AUTH TOKEN”.

twilio-account

Now download and install Twilio connector into Anypoint studio.

Anypoint Studio –>Help –>Install New Software

twilio-connector

Configure pom.xml to pull Twilio jar dependency in maven based project.

Add plugin in plugin section and dependency in pom.xml file. This section will also add into pom.xml file when Twilio connector drag into AnypointStudio canvas and use it into flow.

<plugin>
   <groupId>org.mule.tools.maven</groupId>
<artifactId>mule-app-maven-plugin</artifactId>
<version>${mule.tools.version}</version>
<extensions>true</extensions>
<configuration>
<copyToAppsDirectory>true</copyToAppsDirectory>
<inclusions>
<inclusion>
<groupId>org.mule.modules</groupId>
<artifactId>mule-module-apikit</artifactId>
</inclusion>
        <inclusion>
                   <groupId>org.mule.modules</groupId>
                   <artifactId>mule-module-twilio</artifactId>
         </inclusion>
     </inclusions>
</configuration>
</plugin>

Dependency tag

<dependency>
<groupId>org.mule.modules</groupId>
<artifactId>mule-module-twilio</artifactId>
<version>1.4</version>
</dependency>

Now configure Twilio Global Elements to connect your application with Twilio into Mule-config.xml file

<twilio:config name="Twilio" accountSid="${TwilioSID}" authToken="${TwilioAuthToken}" doc:name="Twilio">
<twilio:http-callback-config />
</twilio:config>

In above code TwilioSID and TwilioAuthToken are coming from Twilio account.

Mulesoft Twilio connector provides a  number of methods to integrate with your application. Below image show some of methods expose by Mulesoft-Twilio connector.

twilio-method

I am using “send SMS message” method form Mulesoft-Twilio connector for my example.

Now you can integrate Twilio to send SMS with your application. Here is example code.

<logger message="#[payload.recipientPhoneNumber]" level="INFO" doc:name="Logger"/>
<twilio:send-sms-message config-ref="Twilio" accountSid="${TwilioSID}" body="Hello World Sending SMS from Twilio" from="+15555555555" to="#[payload.recipientPhoneNumber]" doc:name="Twilio"/>

Twilio API does not support bulk SMS for recipient. So, to initiate messages to a list of recipients, you must make a request for each number to which you would like to send a message. The best way to do this is to build an array of the recipients and iterate through each phone number.

Here is small flow for Twilio integration.

twilio-flow

Code for this flow.

<?xml version="1.0" encoding="UTF-8"?>
<mule xmlns:twilio="http://www.mulesoft.org/schema/mule/twilio" xmlns:http="http://www.mulesoft.org/schema/mule/http" xmlns="http://www.mulesoft.org/schema/mule/core" xmlns:doc="http://www.mulesoft.org/schema/mule/documentation"
xmlns:spring="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-current.xsd
http://www.mulesoft.org/schema/mule/core http://www.mulesoft.org/schema/mule/core/current/mule.xsd
http://www.mulesoft.org/schema/mule/http http://www.mulesoft.org/schema/mule/http/current/mule-http.xsd
http://www.mulesoft.org/schema/mule/twilio http://www.mulesoft.org/schema/mule/twilio/current/mule-twilio.xsd">

<http:listener-config name="HTTP_Listener_Configuration" host="0.0.0.0" port="8081" doc:name="HTTP Listener Configuration"/>
<twilio:config name="Twilio" accountSid="${TwilioSID}" authToken="${TwilioAuthToken}" doc:name="Twilio">
    <twilio:http-callback-config />
</twilio:config>
  <flow name="twilio-mulesoftFlow">
     <http:listener config-ref="HTTP_Listener_Configuration" path="/twilio" doc:name="HTTP"/>
     <set-payload value="" doc:name="Set Payload"/>
     <logger message="#[payload.recipientPhoneNumber]" level="INFO" doc:name="Logger"/>
     <twilio:send-sms-message config-ref="Twilio" acc#[payload.recipientPhoneNumber]: #339966;">${TwilioSID}" body="#[payload]" from="+15555555555" to="+12222222222" doc:name="Twilio"/>
  </flow>
</mule>

If you are getting exception, make sure twilio-mulesoft jar is in classpath and properly configured.