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Impact of 5G on analytics, computing and AI – Free Press Journal

From the government perspective, there will be several new smart city solutions that will be supported by 5G. | File Photo

India made a significant leap in mobile technology recently when the Communications Minister, Ashwini Vaishnaw, made the first call using 5G Technology. It’s a proud moment for India as the entire end-to-end network was designed and developed in India.

5G is the fifth generation mobile network for wireless communication after 4G. 5G technology is expected to significantly boost the economy as new applications and devices will come into mainstream use. Few examples include Connected Cars, Augmented Reality, and Advanced Drones.

From the government perspective, there will be several new smart city solutions that will be supported by 5G. It is estimated that by the year 2035, the technology will make a $1 trillion economic impact in India. However, to make this happen telecom providers will first have to make significant investments in licensing the spectrum and setting up infrastructure for support.

With 5G technology, internet speeds are expected to increase 10-20 times, and more devices including IoT will be enabled through increased network capacity and low latency. This transition to 5G is going to positively impact companies and government organizations across the world. Over 100 countries are currently testing or deploying 5G technology and are trying to be at the forefront of this transition to unlock the economic value as fast as possible.

With 5G technology, massive amount of data will be generated that needs to be processed at low latency. Imagine two cars on a highway that are able to communicate with each other to avoid collision. This is possible only with 5G technology as 4G cannot provide low latency for cars to communicate their location or speed and get a response quickly.

However, this processing needs to happen at a location close to the cars referred to as the Edge. Edge Computing is the processing of data closer to the device at the edge of the network to provide low latency and real time response. Certain cases in which extremely quick response is needed, processing cannot happen at centralized data centers or Public Cloud far away from the device.

Other examples where Edge Computing is needed includes Augment Reality or Virtual Reality in which the device might not be able to support all the processing capabilities. Public Cloud or Centralized Computing located far away from the device will not support applications running on these devices. With high latency or lag in experience, Virtual Reality and Augment Reality applications will not function smoothly and the users will experience nausea.

Companies have to make critical decisions about what data will be processed at the Edge vs. Cloud but numerous companies are not yet prepared as there is a lack of awareness. Clear guidelines on what data should be processed using Edge Computing vs Cloud is, hence, needed. Telecom companies and Cloud providers could potentially partner to increase the awareness of Edge Computing going forward.

Simple rule to follow

Edge Computing is essential to lower the computation costs, provide low latency solutions, handle device management, manage device analytics and Caching. Cloud Computing will continue to be utilized for Big Data Analytics, Data Warehousing and Business Logic.

With Edge Computing, precious data might not be captured if data is not sent to Centralized Cloud. Therefore, companies have to make these trade-offs to manage costs, ensure low latency and capture valuable data. The biggest challenge for companies is to predict what data could be useful in the future. If they don’t collect important data, it’s a lost opportunity as that precious data could be powering Artificial Intelligence models in future. Companies therefore, have to rethink their entire data management strategy to manage these tough tradeoffs.

To conclude, companies have to first question themselves how 5G is going to impact their business model, products and users. Once companies identify the need for low latency solutions and IoT devices as part of their offering, they can then start thinking about Edge Computing. Companies can then start adding more resources to build the capacity for computing on the Edge. Lastly, companies have to develop a plan to map all data sources, identify data to be collected at each of the sources and filter the data sent to centralized Cloud. Following these basic guidelines will significantly help companies to unlock value for themselves as well as for the users in the world of 5G.

(Harish Srigiriraju, Principal Engineer at Verizon)

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This UrIoTNews article is syndicated fromGoogle News

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