How to Self-Quantify a Network Using Internet of Things (IoT)

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Recently, I have posted the concept of Shadow Network that intelligently sense and adapts its network characteristics to its surroundings. I began to realise that this concept is quite similar to the Quantified-Self whereby sensors are being used to collect data regarding the individual and track his health, productivity, social life and habits. With the information gathered via these Quantified-Self tools, the person will know a lot better about himself and thus can change his lifestyle habit to be healthier and productive.

It’s quite similar to the Shadow Network; it will use the surrounding sensors i.e. smartphones or dedicated sensors to collect data and later make a decision by itself how best to serve the users connected to it.

That’s why I termed Shadow Network as a “Self-Quantified Network

Now, imagine a network is just like a “human” trying to make himself more “healthy”, “Sociable”, “good mood”, “more productive”, “enjoy hobbies”, “enjoy the travels” – And what if the network is also capable of improving itself by having “better coverage”, “providing good QoS’, “give better capacity”, “understand the situation”, etc?

The question is – where does it learn from? Previously, network learns from its network traffic condition which either collects its “throughput”, “latency”, “error-rate”, etc. But with the era of Internet of Things (IOT), sensors are now available everywhere. What if these sensors provide that extra information to the network? The context information can be in many forms, such as:-

  1. Spatial – Location, Speed, Orientation
  2. Temporal – Time and Duration
  3. Environmental – Temperature, Light, Noise Level
  4. User Characterisation – Mobility Pattern, Social interactions
  5. Device Resource Availability – Battery Power, Computational, Storage, etc.

And now – just imagine if you can harness the data and turn into knowledge that will allow the network to be re-configurable (we termed as Self-Reconfigurable Network). It will transform the network to be more intelligent and adapts to its surroundings and give a better service to the users attached to it. We called this – Shadow Network.

About the Author: 

Mazlan-Abbas-e1468839685939Dr. Mazlan is ranked No. 20th Thought Leader in IoT by 2014 Onalytics Report – “The Internet of Things – Top 100 Thought Leaders” , ranked Top 100 in Smart Cities Top Experts by Agilience Authority Index May 2016 and ranked 2016 Top 100 IoT Influencers by Postcsapes. He is currently the CEO of REDtone IOT and is a public speaker at leading IoT events. You can get in touch with him on LinkedInFacebook, and Twitter.

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