Edge computing is one of the emerging revolutionary technologies that will help businesses further improve their operations and network. Anupam Kulkarni, CEO & director of iauro Systems, discusses how by breaking free from the traditional cloud-based network limitations, businesses will be empowered with endless possibilities to re-imagine the user experiences, products & services, and operational excellence.
One of the new revolutionary technologies, Edge Computing, is just what might be needed to explore the possibilities well beyond the limitations of traditional cloud-based networks. Edge Computing is data analysis to the closest point of interaction on a device in real-time. Anupam Kulkarni, CEO & Director, iauro Systems Pvt. Ltd. shares how getting the data center closer to the data can help resolve decisive challenges of cost, flexibility, bandwidth, latency, congestion and data sovereignty across a broad range of IoT applications.
Why Is Edge Computing Relevant Now?
Entrenched in decades-old remote computing ideas, the concept of edge computing has always been here; but for us to move forward to the new technological generation, we have to take advantage of all that IoT offers. Many IoT devices consumers use can be considered edges, from a Fitbit measuring your fitness to a Nest Thermostat controlling the temperature in your home and from drone-enabled crop management to smart utility grid analysis.
Today, data is being produced at speeds never seen before, rendering traditional data centers’ infrastructures unable to accommodate, resulting in strain on the global internet. The past decade or two has seen a significant shift from on-premise computing to cloud computing; the coming years will see a similar transition to edge computing as it happens closer to the action of its recording and undoubtedly wins over cloud computing in regards to time-sensitive events.
Today, over 90% of data is created and processed in centralized data centers. This figure is said to drop down to 25% by 2025, as predicted by Gartner.
See More: Top 10 Edge Computing Platforms in 2022
Benefits of Edge Computing
With a market reach of $250 billion by 2024, as forecasted by IDC, global edge computing holds the key to digital transformation by enhancing industries’ operational efficiency and performance and ensuring data safety.
1. Lower Latency
Speed plays a vital role in using edge computing as the longer it takes to process data, the less applicable it is. Data processing at the edge reduces or eliminates data travel, thus accelerating data transfer.
Edge Computing makes your data relevant, valuable and actionable resulting in faster response time. Every second matters, especially in the case of self-driving vehicles, where a second is all it takes for everything to go wrong. It’s also equally relevant in factories to reduce the number of on-site injuries by detecting human flesh.
2. Outage Reduction
Pushing all the data to the Cloud can cause a traffic load leading to ISP failures and cloud server downtime. This could be detrimental to many severe operations like railroads, chemical plants and/or digital factories. Edge Computing reduces the traffic load and improves the performance of all your industrial applications and services by guaranteeing uptime.
An outage can severely impact a company’s operations and growth, as happened with CES in 2018, which proves how crucial Edge computing is as it reduces the chances of outages.
3. Wider Reach
Unlike Cloud Computing, where access to the internet is a must to process data, Edge Computing can process data locally, without having to access the internet, thus increasing the range of computing to remote and inaccessible locations which were otherwise not possible to access.
4. Process Optimization
If you were to ask a question to ‘Siri’ or ‘Alexa,’ the response time is more as it requires them to source the data from the data center and then transfer it back to you. Similarly, in factories or at TSA checkpoints, having cloud computing would push all the data to the Cloud making it difficult to extract it when required.
If it were to use Edge Computing instead of Cloud, data centers would be able to implement time-sensitive rules to stream data to the Cloud in lots when bandwidth requirement isn’t as high. If a pedestrian were to walk in front of a self-driving car, it needs to react to it (external factor) in real-time and not wait to send a signal to the Cloud and then wait again for a response- the process needs to happen at once which is why process optimization is of core importance if we are looking at a tech-savvy future.
5. Reduced Cost
Not all data acquired is relevant, so spending money on all of it isn’t justified when transporting, managing and storing it. Edge Computing allows you to classify and retain essential data, granting organizations higher bandwidth and storage at lower costs.
It doesn’t diminish the need for the Cloud but instead optimizes the data flow to minimize data costs and eliminate data redundancy resulting in a fall in the amount of data traveled, managed and stored.
Reliability & Security
The world is a large place that includes less than optimal environments for internet connectivity. Because processing happens at the edge, prefabricated micro data centers can locally store and process data without the internet is an issue to do the same in just about any environment, making Edge Computing highly reliable.
Moreover, the data collected at its source is kept and computed inside the local area network and the company’s firewall. It ensures reduced exposure of sensitive data and complies with the ever-changing data laws.
What’s Next for Edge Computing
Like global warming, cloud computing is here to stay for a long time. While ‘Edge Computing’ certainly has the edge over ‘Cloud Computing,’ it still has a long way to become as omnipresent as the Cloud is. It’s no doubt that they have a variety of benefits and use cases and can work together to bring in a vast difference. But it’s only a matter of time for businesses to learn how Edge computing can speed up the operations and scale down the usual risk factors.