Cognitive networks are multiple transmitters and receivers that communicate at scale over long distances. However, rather than the network being defined by hardware devices, cognitive networks are defined by software. The addition of sensors to the hardware, which are controlled by software, creates a smart wireless framework that integrates network functionality into wireless link modules. This hardware-software combination in a cognitive network paradigm allows for the network to perceive current network conditions; plan, decide, and act on those conditions, as well as learn from the consequences of its actions, all while following end-to-end goals. The additional ability of the network to have a cognitive loop system allows it to sense the network status and adjust to any changes in the status. These features are what separate cognitive networks from regular networks.
Once a network has been set up via software coding to sense its environment, a whole new world opens up for analytics thanks to artificial intelligence. Computers will be able to self-diagnose their environment, predict potential future issues and automatically course correct networking issues depending on a number of parameters as defined by or allowed by the human operator. Time and resources will be reduced dramatically because human error and troubleshooting initiatives will be eliminated entirely, while overall network connectively will be dramatically increased.
Numerous advantages of cognitive networking’s impact on the educational environment exist. As educational video and gaming applications are used to enrich learning, network performance can be a huge challenge. Cognitive networks can provide granular visibility and control over applications and how they are performing. It can autonomously adjust for steaming video traffic like ESPN3 by throttling it back, while prioritizing and allocating more bandwidth for critical learning and VoIP type applications. This helps enhance the learning environment as we migrate away from traditional classrooms to a more digitally content aware mobile learning/teaching environment. Moreover, with the advent of the Internet of Things (IoT) the cognitive network can enhance access and control over critical campus infrastructure, such as supervising and controlling meters, lights, pumps, motors, generators, steam plants, and chillers, while simultaneously servicing multiple applications, such as Google Docs, Office 365, real-time educational testing apps and IP surveillance video.”
For specific information about Cognitive Networks on the Education sector, please visit www.pcmg.com.
About the Author:
SVP and General Manager SLED
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