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FogHorn 2020 Predictions: Edge Computing in 2020 - What is it, where is it, and why is it important?

VMblog Predictions 2020 

Industry executives and experts share their predictions for 2020.  Read them in this 12th annual VMblog.com series exclusive.

By Sastry Malladi, CTO, FogHorn

Edge Computing in 2020 - What is it, where is it, and why is it important?

Over the past year, many industry players increased their focus on edge-based solutions, and organizations are now beginning to understand the value true edge computing can bring to their Internet of Things (IoT) and Industrial Internet of Things (IIoT) projects. For example, for automotive and transport-focused use cases, edge computing helps maximize the efficiency and lifespan of battery and charging systems as well as other systems that support braking, motor performance, safety, passenger environment, and predictive maintenance. Moreover, edge solutions enable high-performance processing directly inside fleet vehicles for critical command and control decisions and to minimize the cost and latency associated with uploading huge amounts of data to remote data centers.

In 2020, as more IoT projects move from proof-of-concept to full deployments, keep an eye on these emerging industry trends:

The industry will refine the definition of "edge"

This year many industry players led conversations regarding the exact definition and various locations of the edge.  Organizations have struggled to understand the precise location of the edge when, in reality, the location is highly dynamic and varies by industry and use case. For example, telecom operators consider the edge of the telecom network the true edge (also called the service edge), whereas application developers and industrial plant operators define it as the point of data production (or the location of the asset being monitored). The telco definition of the edge also aligns with MEC (Multi-access Edge Computing).

Moreover, some solutions adopted edge terminology without considering its exact characteristics, thus introducing more confusion to the market. Weak (or fake) edge solutions lack the ability to optimally run analytics and machine learning models on the live streaming data in a constrained compute environment, a crucial requirement for deriving actionable insights in real-time. These solutions are not ‘true edge' as they rely on the cloud for data processing, rather than processing data at the edge.

Lastly, confusion regarding the edge-cloud relationship. Edge is certainly complementary to cloud, although in the industrial sector, edge greatly enhances the cloud adoption and value. Indeed, over the next year, edge computing leaders will continuously work to evolve and refine answers to questions such as: where is the edge located, what is edge computing; and why is the edge important.

Automotive manufacturers will look to edge computing to improve real-time functionalities and accelerate autonomous operations

Cars generate significantly more data today than ever before, and it is a big challenge to gather, merge, process, and deploy all that sensor data efficiently. The future of transportation with autonomous vehicles (AV) depends on creating the required intelligence and processing to build and operate sophisticated, autonomous systems. For example, many AVs are expected to be electric cars, and these will require substantially more in-vehicle intelligence and system life cycle management. These are needed to maximize the efficiency and lifespan of battery and charging systems, as well as other systems supporting braking, motor performance, safety, passenger environment, and predictive maintenance.

While fully autonomous vehicle controls are years away, there are many existing edge computing applications now available to enhance the efficiency, reliability, and safety of commercial and public transportation. These include vehicle control and safety systems, such as cameras, driver assistance, and collision avoidance functions, that are being added to new vehicles every year.

In the year ahead, rather than relying on remote data centers for critical command and control decisions, automotive manufacturers can eliminate safety concerns and fast-track the road to autonomous driving by deploying edge-enabled systems.

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About the Author

Sastry Malladi 

As CTO of FogHorn, Sastry is responsible for and oversees all technology and product development. Sastry is a results driven technology executive with deep technology and management experience of over two and half decades. His areas of expertise include developing, leading and architecting various highly scalable and distributed systems, in the areas of Big Data, SOA, Micro Services Architecture, Application Servers, Java/J2EE/Web Services middleware, and cloud Computing to name a few.

Prior to joining FogHorn as CTO, Sastry was Chief Architect of StubHub, an eBay company where he led the technology architecture transformation and also spearheaded the Big Data initiatives and data driven decisions. Sastry was also a key technology executive at eBay that lead the technology re-platforming effort from its monolithic architecture to the distributed, and scalable service oriented architecture that it is today enabling the business growth.

Published Wednesday, December 04, 2019 8:01 AM by David Marshall
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