How we interact and work has been radically transformed both in business and at home, particularly with the ever-increasing availability of sophisticated internet-enabled devices, applications and sensors over recent years. This transformation is particularly prevalent in the Internet of Things (IoT) where it is triggering an unprecedented data surge which, if harnessed correctly, could redefine how we mine and process information.
Many businesses find themselves with a glut of real-time information but struggle to collate and make sense of all this data. Conventional computing architectures which are based on a centralized data center are no longer fit for purpose, particularly when we factor in bandwidth constraints, low latency and frequent network disruptions.
The solution to this crisis would appear to lie in edge computing which shrinks bandwidth costs related to long distance data transmission and addresses the issue of processing real-time applications at the edge. Recent data released by the International Data Corporation (IDC) indicates that global spending on edge computing is expected to reach $176 billion in 2022, rising by 14.8 percent over 2021. The IDC also projects that spending by enterprise and service providers on hardware, software and edge solution services will continue to sustain the upward trajectory through 2025, when they expect that the figure will reach approximately $274 billion.
What is edge computing?
In basic terms, edge computing is the process of shifting some portion of computation away from the centralized server and bringing it closer to the point where the data is being created. This means that processing and analysis of the raw data is carried out at the edge while information like real-time insights, predictions and other forms of actionable intelligence is dispatched to the main data center. The principal benefits of edge computing lie in minimizing latency and cutting down on backhaul traffic volumes and high costs.
In the telecom sector, edge computing, also known as Mobile Edge Computing (MEC) or Multi-Access Edge Computing, can be used to provide application computation and storage close to the end user’s network. The edge infrastructure itself is generally managed by communication service providers (CSPs) or other service providers. It is important to note that edge computing is not just about MEC but also connectivity and control together with services.
One of the major advantages of edge computing is that it could mitigate network congestion due to the movement of vast amounts of data that modern-day businesses produce and devour. This is achieved by speeding up the movement of data as the latest cutting-edge applications rely on processing and reactions that are acutely time sensitive.
Ismo Matilainen, Marketing Manager, Nokia AirFrame and Edge cloud, further outlined the premise of Edge computing, saying “To run, edge computing requires server hardware, cloud infrastructure software, cloud stack and the application. The hardware needs to be capable of running the application functionality efficiently while the cloud software enables and controls the virtual infrastructure resources to cloud applications.”
Nokia also stated their belief that Edge computing is set to become an integral part of complex business operations as the company expressed concerns that the number of devices connected to the internet is spiking exponentially and the data volumes produced as a result outstrip the handling capacity of conventional servers. This issue is also responsible for placing a huge strain on the global internet at the same time.
Imagine a video camera or a monitor connected to the internet and which is sending live footage and data from a factory or office premises. This in itself is not a problem as the network could conveniently manage the transmission at that level, it would, however, be an entirely different scenario if there were hundreds or thousands of similar devices performing the same function. This latter scenario would not only have an impact on internet quality due to latency but it would also raise bandwidth costs significantly. Nokia, and many other telecommunication companies, hope that Edge-computing will prove to be the answer to this problem by processing and storing data locally.
Advantages of Edge computing
Not only does Edge computing address critical infrastructure challenges such as excessive latency, bandwidth limitations and network congestion it can also lower costs for end users.. It is expected that in the very near future virtually every household and office premises will have installed IoT devices and to support such a complex ecosystem, robust computation capabilities will have to be located to the edge.
The industry believes that edge technology can be of tremendous help in remote areas with patchy connectivity or poor bandwidth while Edge computing can also be used to keep data secure by removing the need to transfer it across large distances through different regions and crossing international boundaries. This is accomplished by keeping data almost at the source, meaning that edge computing can offer relief from a multitude of procedural bottlenecks.
The use of edge computing is not limited to IoT applications as manufacturing and heavy industries employ it for a variety of factory floor operations with the technology facilitating the integration of IoT applications for predictive analysis and maintenance.
In the retail industry, minimal latency could be used to create a rich, interactive shopping experience in stores or even at home with Edge computing helping to create predictive models and identify novel business opportunities by sifting through the diverse data generated by stores and online shops.
Meanwhile in the health sector, data analysis from IoT devices, sensors and other medical equipment will help ensure swift decision-making and effective medical intervention. Other uses of edge computing include such diverse sectors of industry as autonomous vehicles, agriculture, the video and gaming industries and even radio.
The rise of Edge computing also works hand-in-hand with the global roll-out of 5G since the latest standard in wireless communications will also boast high bandwidth and ultra-low latency. To this end, many leading telecommunication companies are fusing edge computing into their 5G rollout since there is considerable overlap between 5G and edge over artificial intelligence and machine learning (AI/ML) Industry 4.0, augmented and virtual reality (AR/VR), automation, self-driving vehicles, IoT etc.
Commenting on the use of edge computing and automation, Ismo Matilainen of Nokia said “Automation is vital to managing thousands of edge sites, enabling 5G cloud-based CSP offerings and future evolution to new business services at the edge. Edge automation with central management provide the required OPEX savings compared to the current crop of centralized data center, where the number of manual operations is still manageable.”