Edge computing in IoT: The Next Big Thing
Edge computing permits data created by the internet of things (IoT) devices to develop closer to where it has being built as an alternative for sending it across long routes to the cloud or data centers. As this computing is being done closer to the edge of the network, it permits the companies to examine relevant information in near real-time – and this has become a need of organizations across numerous industries, including healthcare, manufacturing, telecommunications and finance sectors. Edge computing can be explained as a mesh network of microdata centers that scrutinizes or stores important data locally and thrust all the received data to the hub data center or cloud storage storehouse, in a footprint of less than 100 square feet.
Edge computing is characteristically referred to in IoT use cases, where edge devices can collect data – sometimes enormous amounts of it – and propel it all to a data center or cloud for processing. Edge computing treats the data locally so some of it is manufactured in the vicinity, reducing the backhaul traffic to the essential storage area.
Characteristically, this is done by the IoT devices transporting the data to a local machine that comprises the computer along with storage space and network connectivity in a tiny form factor. Data is concocted at the edge, and all or a section of it is sent to the central processing or storage house in a commercial data center, co-location facility or IaaS cloud.
The benefit of Edge Computing:
According to experts, edge computing exploitations are idyllic in a variety of conditions. One is when IoT devices have reduced connectivity and are not efficient enough for IoT devices to be continually connected to the central cloud. Other issues can be put down to being a latency-sensitive dispensation of data. Edge computing diminishes latency for the reason that data does not have to pass through a network to a cloud or data center for it to be managed. This is perfect for situations where latencies of milliseconds can be unsustainable, such as in manufacturing units or financial services arena.
Example of Edge Computing:
An excellent example of edge computing being deployed can be seen in oil rigs in the ocean that have numerous sensors which are producing vast amounts of data. Most of this data is insignificant; perchance it is data that corroborate systems are functioning appropriately. The acquired information does not necessarily need to be sent over to a network as and when it is being produced so instead they can be sent over to the local edge computing system. This system can assemble the data and send on a daily basis reports to a central data center or cloud for long-term storage. By only sending important information over the network, the edge computing system decreases the data traversing the network.
Difference between Edge and Fog Computing:
As the edge computing market gains momentum there is another technology taking shape, this term related to the edge is called fog computing. Fog addresses to the network connections flanked by edge devices and the cloud. Edge, on the other hand, is more particularly related to the computational processes being done close to the edge devices. Hence, fog comprises edge computing, but fog would also include the network needed to get processed data to its ultimate objective. Supporters of the OpenFog Consortium, an organization headed by Cisco, Microsoft, Intel, Dell EMC and educational institutions like Princeton and Purdue universities, are mounting allusion architectures for fog and edge computing exploitations.
Security Scenario in Edge Computing:
There is two side of edge computing’s security; some dispute that the security is enhanced in an edge computing scenario owing to the fact the data is not peripatetic over a network and is staying close to where it is being created. However, some argue that edge computing is intrinsically less secure because the edge devices themselves can be more susceptible. In crafting any edge or fog computing deployment, security should be a dominant concern.
