Edge in India: Beyond cloud computing & data centers

Edge in India: Beyond cloud computing & data centers

By Indrajeet Ghorpade, General Manager – Technical Services at Rahi Systems

Internet previously ARPANET was a collection of multiple decentralized computers used for communication among various research institutions and in defense. With further developments in centralized networks and commercialization of the internet a centralized network was born. This centralized network is handled by service providers through large colocation facilities.

In India, enterprise data centers have for years been used to fulfill the ever-increasing data requirements of business operations. But as more applications and workloads are moved to the cloud they’re being replaced by cloud computing systems; these systems are hosted in large third party data center colocation facilities in cities such as Mumbai and New Delhi that are also typically home to many network providers. Now with an ever-changing IT infrastructure and need for high-speed data processing, edge computing is supplementing and in some cases replacing cloud and enterprise data center.

What does edge computing offer that cloud and DC cannot?

Cloud computing and huge data centers provide a centralized environment that is effective for a wide range of applications while still being quick enough for applications such as internet searches and social media needs. Their limitation lies in the speed of data, which travels over fiber optic cables at two-thirds the speed of light. That sounds fast, but latency is becoming increasingly crucial since there are a growing number of applications that cannot wait to make a decision while the data they need travels thousands of miles to data centers and back. They need rapid responses in order to make split-second decisions.

Autonomous vehicles, for example, cannot wait 100 milliseconds for data to be transferred to a server farm hundreds of miles away in order to determine whether to change lanes or whether the item in front of the car should be avoided. For an immediate solution, the distance traveled between the data processing unit and the service location should be as short. Edge computing has the ability to attain latency in the single-digit millisecond range, which translates to:

  • Low response times.
  • Enhanced product performance.
  • Scalability.
  • Real-time analytics.

Cloud and colocation facilities currently handle everything from social networking platforms, OTT sites, and online searches for people all over the world. However, because many applications are not time-sensitive, a slight delay in the transmission of data may not be a concern. In the event of latency-intolerant applications, the edge may significantly cut data transmission time to single-digit milliseconds, which will be incredibly effective in the healthcare, finance, and software development industries.

Edge Computing Use Cases

According to Frost & Sullivan’s latest analysis, edge computing will be employed by 90% of enterprises by 2022, with the multi-access edge computing (MEC) sector estimated to reach $7.23 billion by 2024. What are some of the use cases for edge computing in India?

Healthcare IoT

Edge computing will aid healthcare practitioners on numerous levels: using edge devices, it will be simple to build remote monitoring and patient care at the endpoint. On an institutional level, patient data is stored on the cloud, increasing the danger of data breaches. Data security and compliance can be easily maintained on edge by processing and storing data locally on-premise.

Lantronix, for example, delivers the hardware needed to connect medical devices to hospital networks with SGX 5150 IoT Gateway. The multi-interface access allows you to connect numerous device types through the SGX gateway with features, such as secure boot, secure firmware, data-at-rest protection, and role-based access control. The benefit: allowing users to get greater control over their network endpoints

Traffic management with edge

Traffic management and surveillance are another example of low latency applications. When a monitoring system is implemented at the edge, bandwidth costs can be lowered by up to 70%.

Edge computing applications here include:

  • Automatic Number Plate Recognition (ANPR)
  • Intelligent Video Analytics (IVA)
  • Facial Recognition System (FRS)

Another use: customer demand can be tracked in order to improve bus frequency with edge. When data processing is done at the edge, vehicle flow control and lane management systems will be significantly more effective.

With more cars on the road than ever before, intelligent traffic management is the need of the day. Intel’s OpenVINO toolkit, for example, can be used to develop ITM that leverages edge analytics and utilizes traffic camera networks in generating alerts easing transportation and road management.

Efficient industrial manufacturing with edge 

For many years, the industrial world depended on traditional technologies to make choices that were not data-driven. Implementing edge in the industrial industry will be immensely valuable for forecasting maintenance, machine malfunctions, and achieving energy efficiency targets. Real-time analysis would also enable manufacturers to tailor their products to meet the needs of their customers.

Manufacturing and processing industries are collecting data from their plants at an individual level, making it a time consuming and complicated process that requires lots of programming and maintenance. Industrial edge devices collect data from machines and edge applications. A central management system provides easy deployments, complete administration, and instant updates.

Edge for fintech

The most important factor in gaining a competitive advantage over other financial service providers is speed. Because there is a growing need among customers for speedier financial transactions, banks may leverage edge computing to provide faster and more secure services while ensuring regulatory compliance and fraud detection.

Hedge funds and High Frequency Algorithmic Trading (HFT) organizations are looking for strategies to reduce their current last-mile data delay. Local data processing can help these businesses distribute data more quickly by minimizing data delays across colocated server farms in remote locations, boosting revenue.

AR, VR & Mixed Reality 

While we all appreciate the interactive filters on Instagram and Snapchat, AR inserts digital components in the actual world, as opposed to VR, which creates a fully virtual environment. Augmented reality is created using smartphones or wearable gadgets. After processing, visual components are shown on the device or in the actual world. Without an edge computing architecture, this data would be sent to a centralized colocation server farm, where these digital pieces will be produced before appearing on the device, resulting in augmented visuals that are inefficient, error-prone, and lagging. Edge computing’s low latency allows data to be processed locally, enabling enhanced data to be shown smoothly.

Already, AR is no longer restricted to entertainment applications; enterprises all over the globe are using it to display product information to customers in real-time or to show machine information while they are operating. With edge computing, adoption is set to grow more rapidly.

Conclusion

With increased processing demand at the edge and a rapid rise in data utilization, edge computing has reached a tipping point. Cloud computing won’t fade out; rather, network infrastructure will be balanced between edge and cloud computing platforms in the future. If your company relies on data and analytics, working with a data center that harnesses edge capabilities will be a better deal than dealing with traditional service providers.

About the author

Indrajeet Ghorpade is the head of virtualization and Cloud business segment at Rahi Systems in the Rahi Pune office, India. He handles virtualization and cloud computing prospects and contributes to the architecture of enterprise-class IT solutions. He’s an expert in the field with a 16-year background in network security, virtualization, and cloud computing.

DISCLAIMER: Guest posts are submitted content. The views expressed in this blog are that of the author, and don’t necessarily reflect the views of Edge Industry Review (EdgeIR.com).

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