Edge Computing is a computing model that approaches analysis and processing in the place where the data are generated. Thanks to this structure, we avoid their sending to remote infrastructures for their control, considerably improving the response time of applications on devices, in addition to reducing the volume of data sent to the network. In an Edge computing node, processing capacity places the data source as close as possible to said source. We can apply this technology in connected industry machinery, in sensor programmable controllers, in autonomous vehicles … And revolutionise the way in which data are processed!
Electronic devices like smartphones and smart objects have entered our daily life on a mass scale, providing a connection between people and also an interconnection that includes any element present in the environment. The Internet of Things (IoT) stems from the concept of interconnecting everyday objects such as vehicles, home appliances or lighting through the network. According to the latest estimates, in this decade there will be over 20 billion objects connected to the Internet, so we are about to experience a challenge for today’s centralised infrastructures.
The mass deployment of sensors that form part of the Internet of Things, along with the increase in 4K video transmitters, augmented virtual reality and data advances create file traffic on the Internet that grows exponentially. The cloud offers accessibility to transfer, storage and connectivity in a simple and cost-effective, but with an increase like the one foreseen, the time will come when these resources are executed increasingly slowly, creating problems in server performance when the data in the cloud that stores and processes them are distant from the processor infrastructure.
Edge Computing is the paradigm that offers an effective solution to the problem of sending data to the network. Its objective is to carry out prior processing of the data before they are sent, which eliminates any data that are wrong, thereby providing them in a source similar to the one that produces them, giving them format and carry out processing.
Network security is proportional to the amount of data that a system stores in a cloud setting. It is more vulnerable as it processes and agglomerates a larger amount of información. The horizontally decentralised architecture model of Edge Computing establishes the appropriate tools to obtain greater security, considering that edge devices are defenceless before an attack. With the proposal of Edge Computing, companies will be able to filter confidential information and process it locally, subsequently sending only the information that is no longer confidential for analysis.
The advantages offered by Edge Computing in data processing include the deletion of erroneous readings, which can be compressed or their format amended close to the source.
IoT environments generate huge facility, since they require real time responses and in those that only need sporadic cloud connectivity. The fundamental concept to understanding how Edge Computing will revolutionise information processing is the transfer of the smart part of data centres in the cloud to the devices owned by users, minimising the amount of data that are sent to the cloud.
This reduces the amount of data sent and optimises broadband consumption, storage requirements and computing in cloud infrastructures.
Emerging companies that see the potential of Edge Computing in IoT and that demand real time processing and improved efficiency of collation and analysis propose developing their application ecosystems aimed at computing capacity and storage in devices next to the client.