Internet of Things vs Edge Computing
Today, the terms “Internet of Things” and “Edge computing” are used very popularly. But a lot of us are not familiar with these terms. This is why I dedicated this article to solely understanding the terms and even comparing them. We will examine why some experts believe that Edge computing may replace IoT.
In this article, we will go over various fascinating topics as we compare IoT and edge computing as we go over topics like devices, software, and data processing for both the topics. Hence, sit down, pay attention and satisfy your curiosity by reading till the end of the article.
What is IoT?
Before you read further, look around where you are sitting. Done? I bet that you would have found at least one IoT device! It can be your phone, laptop, TV, personal assistant, bulb, fan, thermostat, speaker, doorbell, camera, or countless others,
Even though the term “Internet of Things” was coined just 16 years ago, there are more than 13 billion IoT devices! If you want to define IoT very crudely, you could say that IoT is the ability to connect objects to the cloud.
However, we are not here for crude definitions or layman’s terms. Technically speaking, IoT is the collection of devices with embedded electronics, sensors, actuators, and communication capabilities that allow these appliances to connect, store and share large amounts of data.
What is IoT software?
We know IoT means the network of smart devices that can exchange data autonomously without human interference. However, for an IoT device to work properly, it needs a couple of necessities. These include sensors, protocols, and software.
Let us take a slightly deeper look at these three components:
1. A sensor is for collecting data.
2. The protocol is to communicate and send the data.
3. The software controls or automates the data.
The software enables technology that controls data collection and communication on a connected smart device. The software is the reason the device provides real-time data that computers can transform into information.
Every IoT ecosystem makes use of IoT software. Some real-world IoT ecosystems include smart homes, autonomous cars, security systems, healthcare, agriculture, entertainment, and many more.
What is IoT Hardware?
Since we are on the topic of IoT software, let us also discuss the case of IoT hardware. We have seen that an IoT ecosystem consists of 4 essential interrelated components – sensors/devices, protocol, data processing, and UI (User Interface).
It is the sensors in the hardware components that convert information obtained in the outer world into data for analysis. These include data regarding the process or environmental surroundings like temperature, fluid flow in the pipe, air quality, and infinite more examples.
When we say ‘hardware’, we mean the entire package. Now, this package may vary by different providers, but essentially, they are all the same. Apart from the devices like sensors and actuators, we must also take into account the wires, the connecting board (breadboard), and the brain that connects to the computer and runs codes.
Yes, the “brain” is the board that directs how the components connected to it are connected by executing computer code. You will get a better understanding of it as we look at some examples of IoT hardware providers.
Data Processing in IoT
Generally, IoT devices don’t process much data locally. Instead, they send the data over the Internet to cloud computers where more resources are available for more sophisticated analysis. Internet-accessible sensors and actuators send sensor data to a data centre somewhere and accept commands flowing downward.
This limits the sampling resolution and sampling frequency of the sensor data, as it requires a significant delay after any event occurs before actions can be taken on the device. One good example is an IoT camera sending relatively low-resolution images to the cloud at relatively low frame rates.
What is Edge Computing?
Now that we are done with IoT let us look at Edge Computing by discussing it along the same lines. In a nutshell, edge computing is a distributed IT (Information Technology) architecture where the client data is processed at the network’s periphery.
To be honest, IoT is getting old. With over ten years and 15 billion IoT devices, IoT overtakes the number of humans on the Internet. But a lot has happened in that time. In modern businesses, data is the lifeblood that provides valuable business insight and supports real-time control over critical business processes and operations.
There are loads of data and vast amounts of data can be routinely collected from sensors and IoT devices operating in real-time from inhospitable operating environments and remote locations almost anywhere in the world.
Instead of transmitting raw data to a central data centre for processing and analysis, edge computing performs this where the data is actually generated. It is one of the many reasons edge computing is reshaping IT and business computing.
What are Edge Computing Devices?
Over time, computers have been getting more powerful. Year after year, computers are becoming smaller and still retaining high-end specs like 64-bit, fully-featured Linux-based edge computers, powerful NVIDIA GPUs, and so on.
Such small-edge devices often have sensors and actuators directly attached to them so that they can take real-world actions in response to real-world events with sub-millisecond latencies.
Since edge computing is all about placing computational resources as close as possible to the data source and where the actions need to occur, we need to place the computer power in the same physical device as the sensors and actuators.
What is Edge Computing Software?
Even though IoT devices run single-purpose single-process software, edge computing devices, on the other hand, run real, modern operating systems, usually based upon the Linux kernel. This helps edge computers to effortlessly multitask, supporting a wide range of popular networking protocols and managing multiple applications simultaneously.
Edge computers have real operating systems that provide many services to applications. Intelligent edge agents can be deployed on them to secure and manage their software autonomously.
In a nutshell, it is easier to keep edge machine software up-to-date than to keep IoT software up-to-date and change the purpose of an edge computer on the fly, or to immediately add new applications to an already existing edge computer in the field.
Edge Data Processing
Let us understand this topic by looking at some examples and what data processing is done on edge computers.
1. Visual Inferencing
As we saw earlier, edge computers are usually fitted with high-resolution cameras that can consume streams of video and perform machine inferencing on this data on the edge machine. This interference can detect the people within the view and sometimes perform more complex inferencing.
2. Anomaly Detection
Just like IoT (and IIoT), edge computers play a significant role in many industrial plants and factories as they can see and hear things that human senses cannot detect. Moreover, as we saw above, edge computers can infer many types of problems and operators.
3. Environment Monitoring
With the help of onboard cameras and sensors, edge computers can also monitor environments for hazardous conditions like particulate pollution or poisonous gases and rapidly act within milliseconds to correct or mitigate while notifying appropriate authorities.
4. Multi-Access Edge Compute
Telco Multi-access Edge Compute (MEC) computers can provide the services that used to be provided in large corporate data centres or public clouds with much lower latencies, as they are physically much closer to customers. In addition, these computers enable any data centre workloads to run on them as they are the same kinds of server-class machines found in large data centres.
Benefits of implementing edge computing in IoT
There are numerous benefits of pairing edge computing with the ever-powerful Internet of Things. Let us take a look at three key benefits:
1. Real-time Latency Reduction
We all know that IoT systems work extensively on data that is collected by the devices in the IoT ecosystem. This data is collected on an hourly or daily basis, or only when triggered by a specific interaction with the device.
With the aid of edge computing, it can provide computing closer to the IoT device, and data collection, and analytics take place at a physically closer location, mostly within the same country or region, perhaps even on the premises, rather than in a large centralized data centre.
2. Helps in optimizing bandwidth usage
We are already aware that IoT devices send very small packets of data back to a data management platform that runs analytics to derive insights. With the help of edge computing, we can enable the processing and filtering of IoT-generated data closer to the devices, optimizing bandwidth by ensuring that only data needed for longer-term storage or analysis is streamed to a centralized management platform.
3. Improving security
By now, everyone knows that the security of IoT is the biggest headache with IoT ecosystems. Though Malware can be used to harness IoT devices to perform DDoS attacks, edge computing is unlikely to be as it is more secure than a private cloud, and it does have the benefit of being more local.
Similarities between IoT and edge computing
A. Sensors: Both these technologies use sensors to gather information that is later used for processing constantly.
B. Data-based technologies: IoT and edge computing are both based on data gathering and analytics. Though, they vary in how they analyze or process data, both of them are heavily dependent on data.
C. Advanced tech: IoT and edge computing are both advanced technologies that have a far-reaching impact on operations across all business spheres.
Summary
Do you see why edge computing may replace IoT in the future? IoT devices are essentially sensors and actuators that do very little local processing as they send data to larger computers in a remote data centre and receive commands from those remote computers.
Edge computers, on the other hand, enable more data to be examined and give faster responses and will continue to migrate ever closer to their data sources. You have now learned what IoT and edge computing are, as we discussed topics like their devices, software, and data processing.