Why Node.js Is the Best Solution for Internet of Things

Introduction

IoT technology is still relatively young and emerged because the market demanded the ability to control various devices, sensors, etc. Every device had its own interface and there was a need in a unified system that would withstand heavy loads of information.

Today more than 50% of companies use the Internet of Things in their product development. More and more developers look for the most optimal ways to create IoT platforms, using the best programming languages and tools to design them. As it is a quite new area, there is no ultimate solution, but a lot of companies are looking for the best ways for creating IoT projects. In this article, you will learn about using Node.js in IoT and why it is (in my humble opinion) the future of IoT platforms all around the world. 

Why Node.JS Is the Best Solution for IoT?

In everyday life, you can encounter smart devices more and more frequently. Smartwatches, microwave ovens, laundry machines, and even homes. All of them are harmoniously connected to your smartphone. You simply install an app that helps you control tens of processes that your smart devices are engaged in. This is where the magic of IoT begins. It helps you connect your mobile app with all the smart technology in the house in real-time.

To create such solutions, we have various programming languages: Python, Java, C ++, Ruby. All of them can take care of building IoT platforms, and do a good job. But, if we talk about programming languages that were made specifically for such purposes, all of them hide in the shadow of JavaScript, which is the best for working with IoT. JavaScript itself is not perfect, but here Node.js comes into the game. Node.js has a multimillion community, great number of libraries and ability to work stably on heavy loaded projects, without using much of a server’s resources.

 Node.js logo


Node.js is an environment that executes on the server’s side. Developers use it for creating big and multifunctional projects. It is extremely powerful, and at the same time, easy to learn the tool. Even a developer that is not that familiar with JavaScript can work with it.

First of all, I want to debunk some myths about Node.js left by those who did not look into Changelog Git of repository and have no idea how this technology has developed. So here come some of the most popular myths:

JavaScript is not an object-oriented programming language

Okay, this would sound correct… about 10 years ago. After ECMAscript 6 released, we got full support of classes and inheritance. Sure, it is not the OOP, that we are used to in other programming languages, but no one plans to have typization in JavaScript or access modificators. If you want to have such options — TypeScript is the answer to your problems.

JavaScript doesn’t have an architecture

There is no architecture in JavaScript, so developers write the code as they wish, right? Not exactly. Mainly, this is a problem not only for JavaScript but other powerful programming languages. Anyways, developers have been using programming patterns in their projects. There is quite a big list of popular frameworks for Node.js with their own architectures and rules, so developers have to follow these guides and principles during development.
 
And here is a list of reasons why Node.js in IoT is the best solution for projects development:

  1. Most of IoT projects use MQTT protocol and standard WebSocket, that are great in supporting Node.js.

  2. The package manager (npm) has many libraries especially for working with IoT projects as well as modules for working with devices (Intel IoT Edison, Rasberry Pi or Arduino).

  3. As IoT devices are sensors, transmitters, etc. they usually generate great amount of data and requests as well. Node.js deals with such problems challenges thanks to the ability to support streams (both for reading and for recording).

Common problems that IoT developers face

What is the main concept of the Internet of Things? To connect billions of autonomous devices. As a report of Statista states, there were more than 20 billion in 2017, and we can expect more than 70 billion in 2025.

Security matters

All of these 20-something billion devices are connected to the network and exchange the data they need to function correctly. This data is an attractive prey for dishonest developers, who try to capture the data stream and use it for their own goals.

 

Amazon AWS Security

Image source
For IoT devices security lies in three main components:

  •    Correct and thorough code architecture
  •     Access rights for different types of functional
  •     Verification of devices and users authenticity

Services as AWS have very flexible ways to set certificates and access rights. Most of the developers do not look into it and use only one certificate for everything. Moreover, this certificate has unlimited access to resources and the ability to intercept any data in the system.

Certification should have the highest priority in IoT project development. It is both a simple task that does not require much time and an important one at the same time. If you do not think everything through on this step, there might be a great threat to security. And when the cyber attack comes and most devices stop working, all you are left with are broken pots and a certification that you should have taken care for.

AI threat

Another big problem is artificial intelligence (no matter how strange it may sound). Developers use AI to simplify the processing of large amounts of data. It helps automate many processes and make the developer’s life easier. In this case, developers need to constantly modify these algorithms and can never be certain what they just uploaded to the system. With a minor human intervention, some of the variables can accidentally correlate with each other and it is hard to predict the consequences.

Not understanding the ways IoT works

If you only learn the basics of the Internet of Things development and feel ready to start working on a big project — you better start with something small. At the end of the day, your lack of experience may harm not only your reputation as a developer but also the whole company.

Where to start IoT project development on Node.js

Where to start IoT project

 

The first question you have, when starting the work on IoT project: where do you start? Do you create an architecture, or do you choose all the modules you need? Maybe you begin with a database?

It is all much easier than it may seem. The first thing you do is create a general architecture of databases and all the fields. You will need it for the best optimization of your project. Without it, you may get slow requests or even get stuck in the middle of development because of the bad system architecture. Databases are the most vulnerable place in IoT projects that is very hard to change in the process. Architecture should be as flexible as possible and optimized for the integration of new functionality.

The best way is to use a pattern HMVC (Hierarchical Model – View – Controller) where each system component has its role in the grander scheme and MVC architecture that is familiar to all.HMVC ModelImage source

After you come up with database architecture, you need to think of the way the data will update, with what frequency and what will be their number. Mostly IoT services have a prepared solution for your problem. For example, AWS IoT has a function ‘Rules’ with which a developer or a DevOps can organize the data. There you can choose where to store your data, in which database, which script to run for additional data processing, etc. You need to be very familiar with the service’s functionality, so you will never get in the situation where you reinvent the wheel. Services like ASW are meant to make your life easier, and it a big miss if you don’t use them.

How to choose the right database for IoT

Modern databases support IoT databases, and all depends on just how a developer is going to implement this connection. Before choosing a database, you need to find out if it suits the functionality you will provide the users. Here is a list of main functional the database should have:

  • Flexible architecture and supports indexes
  • Withstands heavy loads of information
  • User-friendly scheme
  • Supports data export and import
  • Multifunctional search by various parameters
  • Security
  • Good balance of price and quality

When it comes to kicking off the development of IoT project, it is up to every individual which characteristics to set as the highest priority. It is not bad to use a couple of databases for your projects, though. Sometimes the projects might have such a complex architecture that only one database cannot satisfy all the functionality needs. Important to know: you don’t need a powerful database for a simple task; just use a highly specialized one.

InfluxDB InfluxDB is the best database for IoT development since 2013. It is a time-series database with an open-source code written in Go programming language. It is perfectly optimized for IoT, which helped it gain such popularity until this day.
CrateDB

CradeDB is a distributive of SQL database with an open-source code written in Java. Its great benefit is a list of libraries it includes: Facebook Presto, Apache Lucene or ElasticSearch that don’t require any further configuration and will make your life much easier. This database is great for integration into IoT platforms of different complexity.

MongoDB

MongoDB is a NoSQL database with an open-source code. It is the best friend to every developer that has written at least one project on Node.js. It is easy to learn, and it has JSON-like architecture that combines well with a JavaScript code. MongoDB may be not the best solution for developing an IoT platform, but instead, it is for Node.js integration on the platform.

Amazon DynamoDB Amazon DynamoDB is a time series database with closed source code and is among Amazon web services. As other analogs (Cloud Bigtable or IBM Informix), it is better to use with other services that the company offers. In this case, AWS IoT with DynamoDB gives you a highly effective platform to develop heavy loaded IoT projects. It is a bad decision to use this database separately, but there are many other analogs out there that can give the same result.

What conclusion can we make after comparing different modern IoT databases? They all are suitable for IoT platform development, but each one of them has its own tricks up the sleeve. So choose wisely depending on your needs.

How to optimize Big Data in IoT projects

So we chose the main technology stack in our IoT project, thought through the architecture of both databases and servers, and now it’s time to begin the development. First thing you do is define which part of the project will have the most loading and how to optimize this part. If you use a complex solution (AWS IoT and DynamoDB for example), in this case, AWS will take the most loading, so you can be sure that all your data will be processed correctly, no matter the number. On the other hand, if we create the architecture on our own server, there are a couple of solutions that will help us.

Let’s keep in mind a few helpful things that will make your optimization less painful:

The future architecture is able to grow with the project

 Most developers use Docker containers and Load Balancer that help scale the project automatically. No matter what you choose AWS ECS orHAProxy, you need how this technology works, how to set it and what to do for its maintenance. Many development problems occur because the developer doesn’t know how to configure the system that community has recommended. Everyone chooses what suits their needs the best.

Next step in optimization is the work with the project's code

You need to know how Node.js works, what are the strong sides and weaknesses. The best way to work with Big Data is to create an architecture that is responsible for a small part of a project and nothing more. The projects have to log its result and have an option to check the functionality in closed sandboxes. You need to understand that Node.js in IoT offers the developer different ways to solve the problem, so it’s better to stick with the best practices of working with heavy loaded systems:

  • Code has to process heavy operations through a queue
  • Your project needs to have data cashing
  • The requests for the database should be as optimized as possible

If you keep your architecture simple and use these best practices — you can be certain that your IoT platform will be fast and stable no matter how much data it processes.

IoT analytics in real-time

In most cases, the main purpose of the IoT platform is to collect analytics from hundreds or even thousands of sensors and show this info to users. In the modern world, everything has to work in real-time and to have a nice and simple interface to showcase this data. Analytics development is a great challenge for those who balance between working fast and keeping it easy in production. Many think that it is better to use a preset solution and set it for your project's needs. It is the right way if there is no highly specific functionality in your project. Somebody somewhere may have faced your problems and already developed a solution. So why not to use it? On the other hand, no IoT projects are the same, so you always need to think of the specifics of your product.

IoT Analytics
Photo by Adeolu Eletu on Unsplash

If there is a need for developing real-time analytics, and you are short on time, better just use services as AWS. Also, you can always count on the internet and find some solutions with open-source code, so you can quickly integrate module into the system and use it.

Sure, you can connect the web client to IoT and output the data directly, but there might be issues with security. It is important to understand what you give the users, how they should authorize, and if the system can control the users and their access level. The best way is to divide the IoT separately WebSocket on the server which will filter the data and will have no way to affect the IoT directly. You also need to keep in your mind the fact that during the development of data transmission through WebSocket, you need to be aware of memory leaks. Also, try not to overcomplicate operations with the preparation and transfer of data to the analytics.

All the JavaScript operations in the browser are based on the browser capacity. If the data flow is too big, the browser can slow down, or even crash. It is not a problem for the experienced developers, as they know how to handle queues, cash, and data filtration. You always need to think of the audience that your project is meant to work for and optimize everything to their needs. Most developers create SPA(Single Page Application) web applications based on popular frameworks or libraries (Angular or React).

Conclusion

In this article, I did my best to explain many different aspects of IoT projects development, which can be used for heavy loaded platforms. In the first place, developers need to realize that functionality that IoT platform requires, using the options they have access to.

Programming world does not stand still and every day new solutions for resolving different problems emerge. You always need to be aware of all the new things that appear, or otherwise, you will stay behind. IoT platform teaches you how to be disciplined and does not forgive mistakes easily. Losing data or it's not correct processing might lead to really bad consequences for the company and all the users that trusted the solution.

Developers team always needs to approach the development the best way they can, predicting all the problems the platform might run into. First thing first, define the architecture, what external solutions to use and how to handle them. You can never be certain if your solution is fully functional, but it’s better to make sure than to test it on a project with real data. Of course, it is not always right, some cases require developers to go against the rules, but they need to justify the goal that the developers have set.

Never stick to one technology or service and always be open-minded to new things. Maybe a new library or framework is a solution for all the problems you were struggling with using old technologies. Decide how you will try this out, because one way or another, Big Data is not easy to develop and check if everything is going right. Just approach everything carefully and you are safe.

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