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What is Edge Computing and why do we need it?

Edge Computing is a powerful paradigm in the M2M ecosystem that harnesses the local processing power of black boxes and smart devices in order to make cloud computing a more streamlined and reliable experience. In brief, edge computing is all about reduced data transmission.

As black boxes and other connected devices have exponentially increased in processing power and memory over the last decade, a new opportunity for cloud computing has arisen. With many devices being now capable of computing power that was unheard of as little as five years ago, it is now possible to streamline the amount of data being transmitted in a given M2M ecosystem by localising the data processing.

By processing large amounts of data locally and only sending the most important pieces of processed information to the central computing environment, the main computer is relieved from having to run unnecessary processes, and a smoother, more reliable data transaction is ensured.

The cost benefits are also huge. Given that network services are generally billed by the volume of use, the relocation of processing to black boxes and smart devices can notably decrease the expenses associated with these services.

The additional security offered by the edge computing paradigm is also noteworthy. With less data being transmitted from black boxes and other devices to and from the core computer, the potential for encryption increases, helping to secure information and prevent the unsolicited interception of information by a third party. Furthermore, this finite pool of transmitted data can be more easily subjected to a range of security measures such as firewalls, enabling the central computing environment to efficiently identify and exclude viruses and other forms of malware.

 

How Edge Computing Plays out in the Industrial Internet
& Subnet of Things

A Subnet of Things (SoT) denotes a single cluster of devices and objects that link together intimately online to serve one or multiple functions. An example of this might be an office WiFi system, where multiple laptops and smart devices connect to routers to assist the employees in a range of work-related tasks.

By contrast, the Industrial Internet of Things (IIoT) is the widespread application of M2M technology in industry, for example in manufacturing, transport or retail. The term emphasises M2M used in business and not so much in a consumer context however, as in the IoT.

An example of IIoT might include the use of smart sensors on trucks across a range of depots that allow vehicles to sense when one or more of its pieces is about to break. A compromised vehicle would transmit this status to the depot’s intelligence centre, which would then automatically dispatch the required replacement piece and arrange for an engineer to be dispatched at corresponding times.

Edge computing therefore becomes more important as the scale and importance of transmissions increase. Indeed, reducing the size of transmissions at a subnet level is certainly essential, but this paradigm in computing becomes even more important and purposeful in an industrial capacity, where the stakes are often much higher.

 

Consultancy

If you need to get a locational M2M project off the ground quickly and don’t have the time to learn map-based analysis, then our consultancy services could be the right solution for you. We offer a comprehensive range of services from geographical data manipulation and efficient territory management to routing & scheduling, and business intelligence.

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