What is Edge Computing?

Description

Edge computing is a circulated computing model which conveys computer data processing and storage nearer to the location where it is desirable.

• It pushes applications, services, data and computing power outside centralized points to locations closer to the consumer.

• As a replacement of taking a central, remote cloud organizes all the function.

• The data is controlled and put in storage nearby, i.e. on the IoT device itself or at the adjacent network node.

• In edge computing the main computation is completed on distributed device nodes.

• Edge computing does not need contact with any centralized cloud, although it may interact with one.

• Edge application services decrease the volumes of data that must be relocated, the resulting traffic, and the distance the data must travel. That delivers lower potential and decreases transmission costs.

Overview

Edge computing is a revolution in Industry 4.0.

• The increase of IoT devices at the edge of the cloud network is producing a massive amount of data to be computed at data centers, pushing network bandwidth requirements to the limit.

• Despite the improvements in network technology - data centers cannot guarantee acceptable transfer rates and response times ~ which could be a critical requirement for many real time applications.

• Edge computing applications include connected cars, autonomous cars, smart cities, Industry 4.0 industrial manufacturing applications.

• Edge computing is the new generation industrial management technologies which are now a must for industrial manufacturing plants.

• Next equipment coming from Siemens, ABB, GE etc. is all designed & enabled for edge computing.

• These edge devices will communicate in real time with data centers and update operating software, operating conditions on the equipment in real time.

• This will reduce manpower use and cut man hours use by 50 %. It will also reduce breakdowns and improve equipment efficiency to a very high level.

Edge Devices and Field Gateways

A field gateway (edge) is a specialized device-appliance or general-purpose software that acts as a communication enabler and, potentially, as a local device control system and device data processing hub.

• A field gateway can perform local processing and control functions toward the devices; on the other side it can filter or aggregate the device telemetry and thus reduce the amount of data being transferred to the cloud backend.

• Gateways in this context may assist in device provisioning, data filtering, batching and aggregation, buffering of data, protocol translation, and event rules processing.

Drawbacks of pure Cloud Computing when it comes to IoT

Data security threats. Data is constantly being transmitted back and forth between the cloud and a device, and as such, the risk of privacy violation is heightened.

• Performance issues. IoT applications rely heavily on real-time actions. Yet, the processing speed of your cloud-based app often depends on the actual distance between the device itself and the server location.

• Operational costs coincidentally grow as the amount of data produced and shared increases.

• On top of that, most data sourced to the cloud often bears no practical value and is never used.

How does edge computing work?

Every IoT sensor produces tons of data every second. In the case of cloud computing, the data is instantly transferred to the central, unified cloud database where it’s processed and stored.

• If there’s any action required, the central server will send its response back to the device upon receiving and analyzing the acquired data.

• While the whole process typically takes less than a second to complete, there might be situations when the response may be delayed or interrupted. This can happen due to a network glitch, weak internet connection, or simply because the data center is located too far from the device.

• Now, in case of edge computing, you don’t need to send the data acquired by the IoT sensors anywhere. The device itself or the nearest network node (e.g. the router) is responsible for data processing and can respond in a proper manner if action is required.

Edge Computing makes it possible that the IoT device is no longer dependent on the internet connection and can function as a standalone network node

Benefits for edge computing in IoT

1. Increased data security
2. Better app performance
3. Reduced operational costs
4. Improved business efficiency and reliability
5. Unlimited scalability
6. Reliability as edge computing systems provide actions to recover from a failure

Edge Computing Use Cases

Industries with the most edge computing use cases are:

• Travel, transportation, and logistics

• Energy

• Retail

• Healthcare

• Utilities

Efficiency?

• Due to the proximity of the analytical resources to the end users, sophisticated analytical tools and Artificial Intelligence tools can run on the edge of the system.

• This placement at the edge helps to increase operational efficiency and contributes many advantages to the system.

• Additionally, the usage of edge computing as an intermediate stage between client devices and the wider internet results in efficiency savings that can be demonstrated in the following example:

• A client device requires computationally intensive processing on video files to be performed on external servers. By using servers located on a local edge network to perform those computations, the video files only need to be transmitted in the local network. Avoiding transmission over the internet results in significant bandwidth savings and therefore increases efficiency.

Cloud Computing and 5G

• Transporters are deploying 5G wireless technologies all over the world.

• It ensures the benefits of high bandwidth and low latency for applications.

• Many transporters are working edge-computing strategies into their 5G deployments in order to offer faster real time processing, especially for mobile devices, connected cars and self-driving cars.

• Researchers foretell the 5G will be a catalyst for edge-computing.

• Applications using 5G technologies will change traffic demand patterns, providing the biggest driver for edge computing in mobile cellular networks.

• 5G speeds will range from ~50 Mbit/s to over a gigabit/s. The fastest 5G is known as mmWave. There is dire need for on-demand compute and real-time application engagements which would play a role in driving the growth of edge computing in 2020.

• The advance of real-time applications that require local processing and storage capabilities will drive the technology forward over the coming years.

Mansoor Ahmed Chemical Engineer,Web developer