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Edge Computing: Now and Forever

In general, the best vantage point is standing at the front. Enjoying a ceremony or a sports game, you always prefer to be right at the edge of the mob, as near you can be to the ground zero. The same theory is applicable to computing. The best vantage point of your data, in most cases, is nearest to the origin – the device – instead of the data centers.

This is important in manufacturing and for Industrial IoT (IIoT), where you look for minimum delays and swifter processing to ensure a more effective and productive workplace. The caliber to take action on data close to the origin will affect every corner of industrial processes.

Edge computing is a progressive and distributed computing model that decentralizes data processing and storage, thus, bringing it nearer to the data origin. By progressive, it means that the computing occurs nearer to the location of the data created and not on the centralized cloud where the data is transferred over stretchy network routes.

What is Driving Edge Computing?

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The growth of edge computing can be attributed to both the technical and business aspects. On the technical side, this is the product of the snowballing expansion in networking (5G, 100GigE), compute and storage (SSDs) infrastructure that is a part of the Internet of Things (IoT) and mobile computing. From a business point of view, enterprises are continuously hunting for a competitive edge with lower capital investments and enhanced customer interaction.

The burgeoning IoT and mobile use cases have gotten the better of the existing pain-points in the centralized models. It is being utilized to focus on both of these domains. The growth of edge computing is credited to the following factors:

Limitations of Cloud

Cloud is limited by its centralized processing structure that gives rise to security, bandwidth, cost, efficiency, and regulatory issues. A lot of data is being generated today along with insufficient bandwidth to allow all of it to be transferred to the cloud for processing and storage. For dynamic control systems such as, field inventory management, automated vehicles, and business workflow automation, the latency of the cloud network is quite high, and reliability is too low to be practical.

Even though you might be able to solve network latency, reliability, and data volume issues, trying to achieve a centralized compute-process-and-storage framework is a cost-prohibitive affair. To know more about business workflow automation visit Fact.MR.

Mobile and IoT Applications

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The mushrooming growth of mobile and IoT applications continues to accent the demand for low-latency, high-performance, highly accessible, scalable and secure platforms to process all the data that is being produced and used. Despite the basic requisites being the same, mobile and IoT applications have notably outpaced the conventional approaches that were being used to support them.

Architecture to gain Competitive Edge

The emergence of cloud deployment and microservices have begun to turn application deployments into a commoditized activity, with little room for market differentiation. Companies, leveraging it as a competitive advantage, can expand the abilities of their applications by using topologies that can deliver distinct competitiveness.

New Computing Abilities

As of now, we have more storage and compute at the edge, thanks to the evolution of technology over the past three decades. For instance: artificial intelligence (Alexa/Google), and specific processors that can manage local data processing for security (iPhone/Apple). Assigning processing, compute and storage tasks to these new-age devices can cover most of the aforementioned issues, thus, offering a better, and more immersive user and customer interaction at the point of experience (PoE). For more details visit Fact.MR.

Edge Computing in 2020

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The Forrester Analytics Global Business Technographics® Mobility Survey, 2019, revealed that over 50% of mobility decision-makers reported that they have edge computing in their protocol for the next 12 months, which is worth noticing when looking at how lately it rose in the space of technology revolution.

Edge computing is in its early days and has been on a steady rise in maturity and importance. The next year will be full of surprises, especially for players and users in this interesting field. So what is there for edge computing in 2020? Let’s take a sneak peek at some of the predictions:

The market for Edge Cloud Services Will Face a Major Uplift

Platform software providers, data center colocation providers, public mega cloud providers, and telecommunication companies are working on to deliver advanced cloud-native programming services and basic infrastructure-as-a-service (IaaS) on distributed edge computing framework. These service providers aim to deliver IaaS and platform-as-a-service (PaaS) that run with or without intermittent connectivity to data center resources and public cloud. This emerging market will start to witness a mushrooming growth in 2020.

Form, Fit, and Function Will Give Rise to Customized Form Factors

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It’s based on a variety of relevant applications in several industries. The manufacturing of customized form factors, straight from the processor level, will be supported by unique demands of storage, compute and networking for each application. A common instance that we have already come across is HPE venturing a Series C investment of around $145 Mn with the ex-CEO of Cisco, John Chambers’ start-up – Pensando Systems. This collaboration is exposing the market to a customized programmable processor developed for edge computing.

Enterprises Will Prefer Multivendor Packaged Services over Single Vendors

The existing bottlenecks of connectivity and bandwidth are compelling companies to team up with integrators to uphold their edge computing technologies instead of developing and using their own. This is significant for all industries including, transportation, retail, manufacturing, and intralogistics.

Recent surveys suggest that the biggest advantages companies expect from edge computing is the flexibility to manage existing and future AI requisites as well as reduced network latency and quicker responses. Then, there are applications created because of the need for edge computing to handle complex processes, where cloud usually fails, driven by the advancement of connected devices.

Organizations will ramp up investments in and the trend will continue in 2020. The proliferation in edge computing investment is buoyed by the rising maturity of edge platforms, the parallel onset of connected solutions – Wi-Fi 6 and 5G connectivity, and increasing applications for machine learning (ML) and analytics. With the market for edge computing gathering momentum, the time to put edge computing into action is now.

About Suzan Vega

Suzan Vega

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