Digital India initiative by the Government, business imperatives for going digital, an increase in the amount of network exchange and the Covid-19 pandemic have all led to an exponential increase in the demand for the number of data centres.
According to Frost & Sullivan’s latest analysis, edge computing will be employed by 90 per cent of enterprises by 2022, with the multi-access edge computing (MEC) sector estimated to reach $7.23 billion by 2024.
A Markets and Markets report added that the edge data centre market size is expected to grow from USD 7.2 billion in 2021 to USD 19.1 billion by 2026, at a Compound Annual Growth Rate (CAGR) of 21.4 per cent during the forecast period. The COVID-19 pandemic has boosted edge data centre solution adoption across industry verticals as the users move to leverage field service solutions advantages, such as expansions and less cost. Despite the global economic slowdown, around 50 per cent of subscription companies are expanding at a similar pace without any negative influence due to the COVID-19 pandemic.
Edge data centres are seeing an increase in the adoption of the latest technologies in data centres W.Media spoke to Chandra Kishore Prasad, Head IT, IRISET- Ministry of Railways.
“Latency is one of the prime reasons for adoption of edge data centres, along with application requirements and user experience, which demand real-time response. But there are other practicalities. Much of the data generated only has value for a very short time frame. After that, it can be summarised and the vast bulk of it discarded,” said Prasad.
The rise of the edge data centre is about locating IT resources where they are most needed, closest to users, devices, sensors and equipment.
He further explained that the trend of edge data centre and edge cloud is driven by a change in traffic volume and direction. Instead of all data going to and from a central hub, IDC reports that more than half of all data will be generated at the edge of the network by as many as 80 billion Internet of Things (IoT) devices.
The fallout from this trend is that 70 per cent of enterprises will be forced to institute data processing at the edge by 2023. IoT and the growing maturity of artificial intelligence (AI) mean that it is no longer feasible to transmit all that traffic centrally for processing, analysis and action.
Low latency and 5G
Applications such as augmented reality (AR), virtual reality (VR), robotics, 5G, gaming, medical applications, drones, content streaming and interactive entertainment need to low to ultra-low latency and must be processed at the edge. They can’t wait for centralised data centres to control their actions.
“If we take the case of self-driving/connected cars; edge sensors, compute resources and edge data centres are needed to receive, process, analyse, summarise, and transmit both centrally and to the vehicles in the vicinity,” added Prasad.
A modern car is a digital machine with sensors and transmitters. Newer models include imaging systems, radar and LiDAR (light detection and ranging), GPS, self-parking/self-driving functions, collision avoidance, blind-spot monitoring and lane-departure warnings.
Prasad further pointed out that edge compute power is vital in providing the real-time responses needed to make such an intricate system work – and keep everyone safe.
5G will require ultralow latency and newer applications will drive the demand for edge data centres. 5G will require eNodeB almost at every third house/building so it is extremely important to design and build a green edge data centre to lower the carbon footprint and use renewable energy for its operations. The 5G deployment by the Telecom Service Providers will involve the use of street furniture like street lights, parks, gantries etc in the streets and will accelerate the deployment of edge data centres exponentially.
Adoption of AI in Data centres
The adoption of Artificial Intelligence in different enterprises has grown due to the pandemic and a similar trend is seen in data centres.
“Adoption of AI will rise in the data centre as data centre operators continue to automate day-to-day operations. Businesses are more digitally connected than ever before since the lockdown and work from home were put into action. The focus of AI adoption will be in improving the efficiency of data centre operations, enhancing human productivity and cost optimisation,” said Prasad.
Prasad further pointed out that automated systems can be used to predict faults and respond to capacity needs. Advance alerts provide the data centre operation team precious time to respond to the fault, hence reducing the impact of failure.
AI adoption will increase in thermal management-cooling and predictive maintenance in the data centre, power management, workload management and security machine learning can also be deployed along with AI to automatically understand load patterns and predict when fluctuations will occur, as well as for infrastructure operations.
Greater Cloud and AI collaboration, AI in Cybersecurity and AIOps (AI in Datacentre Operations) are becoming more popular.
