Virtualization and Cloud executives share their predictions for 2016. Read them in this 8th Annual VMblog.com series exclusive.
Contributed by Mark Clayman, President and COO of TriCore Solutions
Big Data Becomes Fast and Accelerated with Industrial IoT
Industrial IoT is in the very early stages of deployment. It promises to unlock value and rapidly transform how organizations manage, operationalize, and monetize their assets. With IoT, physical assets become liquid, easily indexed and tracked, enabling identification of idle capacity or over utilization.
IoT is a complex structure of hardware, sensors, applications, analytics and devices that need to be able to communicate geographically and across all functions. Once the data is collected from numerous endpoints, the challenge then becomes converting it into actionable insight. Sorting and analyzing the output from all of these endpoints, and making it relevant for users, is a problem on a scale we have not seen before.
As more organizations embrace the competitive advantages of IoT, they are concerned that their analytical tools and infrastructure will not support this next wave of industrial revolution. The velocity of technological change and the speed of business is outstripping IT’s ability to transform current data infrastructures and business analytics into IoT-ready systems.
It is clear that organizations understand the value of IoT data, but it is unclear how to actually get from collecting the data to deriving value from the data. Until that’s resolved, IoT projects may prove more frustrating than useful.
There are still some major challenges to make the Internet of Things a reality.
Data moves to the edge of the network – Automated data processing capabilities will need to be distributed to the edge of network to process IoT real-time data feeds. As more and more data is generated, current data center gear won’t be able to provide the data and traffic flow capabilities that are required to move quantities of IoT data. By decentralizing core compute and storage resources and pushing them out to the edge, organizations can prevent massive volumes of data from crashing the data center.
Diversified Data – Not only is data growing, it is also diversifying. Organizations require flexibility in handling a variety of data sets including the ability to handle structured, unstructured data, and streaming data with a comprehensive data management strategy. Most data coming from sensors will be structured, in the form of streaming data and it is likely to come from multiple streams. There will be cases where the data coming in will be in the form of images or even video – unstructured.
IoT Accelerates Data Center Evolution – The data center will need to rapidly evolve to handle Big Data generated from IoT applications. Because of the influx of data, higher capacity transport will be required coming in to the data center. In fact, more transport capacity will likely be needed throughout the data center. Computing power and storage will begin to de-centralize and move closer to the edge so the IoT data can be quickly processed closer to the devices and closer to the users who be using that data. Computing will become much more distributed and the delineation between edge and core will become blurred over time.
Data Security – IoT opens up new challenges with privacy and security. Each device with a sensor is a new endpoint on the network which can now be a target for a security breach. Adding hundreds or even thousands of new endpoints creates a security challenge on a scale never seen before. Issues such as how to handle device lifecycle and software updates on a large scale need to be addressed before IoT will ever become mainstream.
We can expect to see every year within the next five to ten years be “The Year of IoT.”
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About the Author
As President and Chief Operating Officer, Mark Clayman is responsible for all Sales, Marketing and Operations at TriCore. He holds a Bachelor of Science in Economics from Penn State University. www.tricoresolutions.com
