by Christian Légaré, Micrium Executive Vice-President
This article is the conclusion to a four-part series.
In Part 1, we reviewed the choices facing an embedded developer who needs to build wireless networking into an IoT device (that is, the Thing in the Internet of Things).
In Part 2, we discussed the different type of IoT devices, and the design choices that you face when designing the hardware and software architectures.
In Part 3, we looked at the Internet itself, how IoT devices make use of it.
In this last segment, we will look at back-end services. Some IoT systems way not need back end services like a smartphone controlling a TV, but the majority of the currently envisioned IoT systems reply on the collection, processing and usage of data by the IoT devices and for this, some form of Information Technology different than embedded systems is required.
The Cloud--This is another interesting buzzword. When I was Director of Engineering at Teleglobe Canada, every time we sat in a meeting room to design a network, we drew it as a cloud. A network is a cloud. The Internet is a cloud. And cloud computing is nothing more than an array of networked computers that allow you to offload processing tasks from your embedded system. The same is true for data storage: why store data locally, when you can store it in a secured data center, with guaranteed power and back-ups?
There is, of course, one fundamental assumption in cloud computing: The network is always available!
So “cloud computing” is a term coined to put a simple name on something that has become very complex. Many companies have launched services that try their best to hide this complexity; these include Apple’s iCloud, Google Cloud Platform, Microsoft SkyDrive, and others. These Cloud computing/storage systems are intended for use with desktop and mobile personal computers. Embedded developers need something similar for IoT devices.
Industry analysts are forecasting the creation of billions of IoT devices by 2020, and these devices will produce huge amounts of data. There are a few approaches for managing and processing all this data.