Modeling the internet of things: a hybrid modeling approach using complex networks and agent-based models

Authored by Muaz A Niazi, Komal Batool

Date Published: 2017

DOI: 10.1186/s40294-017-0043-1

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: ODD Flow charts Mathematical description

Model Code URLs: Model code not found

Abstract

Sensors, coupled with transceivers, have quickly evolved from technologies purely confined to laboratory test beds to workable solutions used across the globe. These mobile and connected devices form the nuts and bolts required to fulfill the vision of the so-called internet of things (IoT). This idea has evolved as a result of proliferation of electronic gadgets fitted with sensors and often being uniquely identifiable (possible with technological solutions such as the use of Radio Frequency Identifiers). While there is a growing need for comprehensive modeling paradigms as well as example case studies for the IoT, currently there is no standard methodology available for modeling such real-world complex IoT-based scenarios. Here, using a combination of complex networks-based and agent-based modeling approaches, we present a novel approach to modeling the IoT. Specifically, the proposed approach uses the Cognitive Agent-Based Computing (CABC) framework to simulate complex IoT networks. We demonstrate modeling of several standard complex network topologies such as lattice, random, small-world, and scale-free networks. To further demonstrate the effectiveness of the proposed approach, we also present a case study and a novel algorithm for autonomous monitoring of power consumption in networked IoT devices. We also discuss and compare the presented approach with previous approaches to modeling. Extensive simulation experiments using several network configurations demonstrate the effectiveness and viability of the proposed approach.

Tags

Complex networks Agent-based modeling algorithms self-organization systems Cognitive agent-based computing wireless sensor networks Internet of things Power consumption