Hands on with IoT, edge computing and cloud computing
Introduction
This blog post is the first in a series of blog posts where we’ll take a look at IoT, edge computing and cloud computing and how these three concepts together could utilize the benefits these technologies bring individually.
What is edge and cloud computing?
The exact definition of many buzzwords are often a little vague and could be interpreted to mean different things depending on who you ask.
What is edge computing and cloud computing? Basically, these are two different ways of storing, managing and processing data. Where cloud computing uses a network of remote servers hosted on the internet, edge computing brings memory and computing power closer to the location where it is needed.
When combining edge and cloud computing together they are heavily depended on the Internet of Things (IoT). Without IoT there wouldn’t be a network of devices to connect these two types of computing powers together. With the growth of IoT a large variety of different connectivity layers and data exchange protocols came with it. This has made the connection of different devices and systems to the internet easier. When we talk about IoT we are talking about a large variety of devices or things connected to the internet.
Why the buzz?
Why all the buzz about where and how your data gets processed? During my Studies in Mechatronics I worked with Microcontrollers like Arduino’s or small computers like Raspberry pi’. These could essentially be considered as edge devices on a small scale, where we rely only on local data and sensors to perform a certain task. With the rise of IoT it has become a trend to connect these devices to the internet and either collect their data into a database in the cloud or control these systems with, for example, a smartphone app.
Edge computing’s main advantages are its ability to perform tasks autonomously and not being susceptible to network problems. Its biggest disadvantages however are the lack of resources in the form of processing power and data storage, and its limitations in using data from outside sources.
Cloud computing’s main advantages are the large amount of processing power and data storage, and the ability to access an unlimited amount of data sources. The biggest disadvantage of cloud computing is its dependency on a reliable network connection for communication with edge devices.
When combining the advantages edge and cloud computing bring together with IoT Networks we keep the speed for autonomous decision making on the edge and use the processing power and ability to acces mulitple data sources of the cloud to analyse larger datasets from single or multiple instances of IoT network(s). To both sides this brings the following advantages:
- Edge computing can utilize the cloud to perform heavier data analytics;
- Cloud computing can enrich edge systems to improve their decision making;
- Both Cloud computing and edge computing can use data from multiple instances of edge systems to form a broader view.
Just like conducting at an orchestra we have the musicians making focused decisions based on its own performance and a conductor orchestrating the whole ensemble based on a larger set of knowledge.
A tangible case for example would be a car (edge device) that sends data to the cloud. There, together with data from multiple other cars, it gets analyzed (cloud computing) to determine if the car needs maintenance or a check up in the near future.
In summary, IoT networks can utilize a mix of edge and cloud computing depended on speed and quantity of data. Where the cloud takes a role as central computing system supervising and/or controlling the edge where necessary, the edge provides the data necessary for the cloud while performing its high speed tasks independent of connection loss or delay.
Let’s get hands on!
To kick off we’ll start off with a pilot project where we can see the power of combining edge computing and cloud computing. For this project we’ll be using a Raspberry Pi and some sensors. The first goal of this project will be to create a prototype that can send data from a Raspberry pi to the cloud. In the next blog post we’ll dive into the code to connect sensors to the Blockbax Platform.
This Blog is part of a series of four blog posts called: combining IoT, edge computing and cloud computing
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