Information-centric framework for the Internet of Things (IoT): Traffic modeling & optimization

With the increased growth in number of connected devices, either static or mobile ones, there is a concurrent massive increase in the accompanied data traffic volume. Therefore, and for better future communication systems with better coverage and capacity performance, the information-centric Internet of Things (IoT), is a prudent option. In this IoT paradigm, populating and reallocating Information Repeaters (IRs) is one promising way in reducing data traffic during the peak periods. Accordingly, a novel placement approach for the IRs in high-demand regions (hotspots) is introduced. Placement of the IRs in these regions is prioritized while sustaining three main objectives which aim at: (i) reducing the network traffic, (ii) maintaining an upper bound for the experienced delay, and (iii) minimizing the average traffic load per publisher. Moreover, this research examines the performability of the IoT paradigm under varying traffic behaviors using a new method in characterizing the network behavior based on Content Demand Ellipses (CDE). Real data-traffics have been used to show how various traffic behaviors can affect key properties/parameters in the proposed CDE representation. And promising results have been achieved.