Edge computing is gradually and profoundly changing the way data is managed. The principle ? Process data as close as possible to the end user or the connected objects that generate it, without having to transfer them to the cloud. The result: a faster, cheaper and more reliable system. We will explain everything to you.
Traditionally, data is stored and processed at two ends of the network :
- either closest to the user, on our computers, smartphones or on the company's local servers,
- either very far from the user, on remote servers within gigantic data centers, in the cloud.
Edge computing defines a third way.
Definition of edge computing
As its name suggests, edge computing consists of processing data in a distributed manner, at the edge of the network, and no longer centrally, in the cloud. It uses mini data centers to store and process data as close as possible to connected objects, end users and businesses. Result: better quality of service by improving latency, throughput, energy consumption and environmental efficiency. Once processed, some of the data may be sent to the cloud for other types of non-urgent processing.
Edge computing is therefore nothing new in itself. Distributed computing has been around for a long time, but its adoption and applications are growing strongly thanks to the rise of connected objects which are straining the bandwidth of networks linked to the cloud.
Ideal for processing data in real time
The cloud faces difficult challenges: processing more and more data and processing it faster and faster. For certain applications (industry, energy production, medicine, road traffic management, etc.), processing time and reaction time are critical. Data must be processed in near real time.
In the industry
The infrastructure solutions company Red Hat provides a good example: in a modern manufacturing plant, around 2,000 Internet of Things (IoT) sensors monitor production. These connected sensors generate around 2,200 terabytes of data per month. A mass of data that can be processed more quickly a few kilometers from the factory than in a data center located on another continent.
In logistics and mobility
Another example: connected vehicles. Buses, trains, trams and trucks are equipped with GPS chips and sensors to monitor traffic in real time and analyze passenger flow. The on-board computer provides information on traffic conditions in real time (accidents, roadworks, blocked roads, etc.). Delivery drivers thus find the fastest routes based on their delivery plan. It's hard to imagine waiting 30 minutes for the route to be updated and then getting stuck in traffic because the data took too long to be sent and processed.
The number and uses of connected objects and the Internet of Things (IoT) are exploding: 13 billion worldwide in 2022, nearly 30 billion in 2030, according to Statista. In France alone, Ademe and Arcep estimate their number at 244 million. These are our phones, our laptops, but also robots, cameras and sensors, those of industry or smart cities. The development of 5G is further accelerating this phenomenon.
And to process all this data, the edge computing solution is essential. The uses of edge computing show growth of 17 % per year, according to the research firm Research & Markets.
By 2025, Gartner estimates that more than 50 % of data managed by businesses will be processed outside of the cloud.
The benefits of edge computing
Reduced communications latency
Processing information as close as possible to its source significantly reduces the time needed to transfer data and respond accordingly. Thus, in the event of a failure on a production line, this will allow IIoT (Industrial Internet of Things) sensors to transmit data and their analysis as quickly as possible.
Higher performance
By transmitting less data to the cloud, data will be processed faster with higher throughput. The company will also be able to cache data in a CDN (content delivery network) integrated into the peripheral network. This will allow content, particularly video, to be distributed more quickly.
Reduced infrastructure costs
By reducing the bandwidth and resources of a data center, edge computing provides substantial savings.
Greater scalability
Distributed edge computing makes it possible to modulate the resources necessary for processing and storing data.
Environmental efficiency
By saving IT resources and reducing the volume of data exchanged, edge computing emits less CO2 and will have less environmental impact.
Edge computing, replacing the cloud?
Edge computing also has its drawbacks. The first is having to use service providers who will offer this edge service. Depending on the location of the company, the choice is not as wide as for cloud providers.
The other disadvantage concerns cyber security. The more information is processed at the periphery, the more complex the architecture becomes. Equipment and service providers are more likely to be heterogeneous. Hardware and processes may be different, with several suppliers... which increases the vulnerability of the architecture.
So edge computing is not a replacement for the cloud. It complements it by handling data with high processing speed requirements. Other types of data, whether less critical or more massive, can continue to be processed in the cloud. So the cloud is not about to disappear.
