Edge Computing uses local devices to compute, store and communicate data. Edge computing can therefore be thought of as an extension of cloud services (which allow compute, storage, analytics, and other functions to be executed remotely) to the user’s local devices, speeding up computation and making it more secure.
So, Cloud Computing + Edge Devices = Edge Computing.
Edge DevicesEdge Devices include routers, routing switches, integrated access devices (IADs) and multiplexers. Edge devices enable users to connect to and share data with an external network — such as a service provider, carrier, or enterprise primary network.
Factors Leading To Edge ComputingEdge computing was driven by the following factors:
Cloud is supported by external data canters, which reduces data transfer speed due to network latency.
2. Limited Bandwidth
In addition to the distance, limited bandwidth further slows cloud data transfer.
Cloud data exchange is often subject to the privacy, security and compliance issues of multiple jurisdictions.
4. Configuration of the System
System integrators are required for cloud to function.
These problems with cloud computing lead to edge computing. The use of edge devices decentralizes cloud functions. These edge devices (like routers) act as facilitators to speed up data processing. So, user devices (like smartphones) can decide whether compute or store locally or send edge devices (like routers) data. Edge devices then decide which information they can process themselves and which information needs to be sent into the cloud for processing. So, many (and ideally most) functions can be performed by user devices and edge devices, with the convenience of cloud processing as necessary.
Internet Of Things (IOT)IoT — the phenomenon of embedding everyday physical objects (like thermostats, toasters and washing machines) with chips, software and sensors — enables these objects to be networked and to perform functions with feedback from one another and without human intervention. These objects thus become ‘smart’.
Since IoT requires the creation and processing of enormous amounts of data, cloud and edge solutions are crucial enablers of IoT (especially in use cases that involve sensitive data or Artificial Intelligence).
Take the example of a driver that wants her vehicle to signal to her house’s garage door that she has arrived. The short time period between her arrival and the garage door’s expected response is a challenge for cloud computing. Even minimal network latency or other network issues would remove the usefulness of IoT solutions here.
Enter edge computing. Most of the information in this transaction can be local, so the centralized cloud environment won’t be necessary in most cases. However, if there is an authentication issue, a cloud solution may be required — and edge computing still allows for this. Additionally, even in cases that cloud is required, it would be accessed at high bandwidth. So, edge computing enables multiple IoT cases.
For a further discussion of the IoT applications that edge computing enables, here is my earlier article describing seven use cases:
A word of caution: these privacy and security gains require significant upgrades in user devices themselves. Most user devices (such as microwaves) use dated firmware and hardware, which makes them insecure and provides an entry point into the network for bad actors. Cloud environments, especially those maintained by Amazon, Google and Microsoft, are generally highly secure. Since realizing the gains of decentralized edge computing requires a new generation of user devices, these gains will likely be realized in the medium or long term.