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Who will benefit more from 5G?

With regard to 5G, much of the mainstream media coverage revolves around the potential market for personal consumption, such as AR/VR games.

But the facts, as many industry analysts observed telecom service providers would have keenly aware that in the future market not from individual users, but from those who participate in the fourth industrial revolution of the enterprise, with large-scale machine type communication (mMTC) and super reliable low latency communications (uRLLC) 5 g services such as Internet companies, Will be the main beneficiary of 5G technology.

▲ Three key core services of 5G

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How to use 5G?

To take advantage of 5G’s key core services, companies will need a true digital transformation. First, don’t confuse digital transformation with existing simple digitization; Second, in response to the digital transformation, the enterprise must consider to reconfigure its business process, to use the machine to machine communication to automate processes, decision and action, thus eliminating potential high price from the artificial operation, at the same time, shorten the time period of value realization, let events data generation closer to the time. The key points connecting businesses are data, business rules, decisions, and actions to match them.

Many enterprises have realized that the speed and low latency of 5G can enhance their competitiveness to a new height. However, to meet the real-time demand, fundamental digital transformation and reform are needed. The definition of real-time is based on two key factors:

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  • Latency: How much time elapsed between the generation of data by the device and the capture of data value

  • Workload: What needs to be done during this delay to extract value information from the data and make a decision

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Complexity V.S. delay

As shown in the figure above, a true event-driven architecture requires more resources than event-driven stream processing for simple aggregation and joins. True real-time workload needs at least seven steps: ingestion, storage, aggregation, key performance indicators measuring, abnormal index (deviation) detection, processing deviation of these complex decisions and take appropriate measures (profit, threat, prevention) is based on the results of the decision step, all these need to be in 10 milliseconds or even a shorter period of time to complete.

If the processing time window is missed, a re-check cycle is entered. Of course, failing to keep up with data processing capabilities can, at worst, completely consume enterprise infrastructure resources, and no one will even know that the data exists, which is a data nightmare for the enterprise.

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Automatic decision making about the system

How does the behavior of the equipment system or human operator affect the automatic decision of the system? It is important for a real-time processing platform not only to process the data stream, but also to push the prepared training data to the machine learning layer to digest or create new data models.

Once a new data model is created, it only needs to be included in the decision process to complete the automatic decision of the system. Usually real-time data processing and automatic update of the model run in parallel with different running cycles:

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  • A cycle is the cycle from event generation to decision action, which Gartner calls a real-time Control Loop.

  • The other cycle is the event learning decision cycle, which combines streaming data with big data, updates the model and manages false-positive or false-negative scenario decisions

Honed in customer and partner application scenarios, VoltDB, originally a distributed in-memory database, has been transformed into a holistic real-time data value management platform that can handle both cycles in a dynamic data flow environment.

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If you’re interested in VoltDB’s Low-latency solutions for big data in the Industrial Internet of Things, or real-time data platform management for the whole life cycle, send us a message and join our official conversation group.