Modelling and analysis of interference diffusion in the internet of things: an epidemic model

Abstract

For the last decades, Internet of Things (IoT) applications have been in high demand with the objective of creating smart environments that could impact positively many aspects of our daily lives. The IoT uses smart objects which are embedded into the environment and interact by transmitting several messages which interference with other messages on receiving nodes. This can lead to inevitable sensors’ (nodes’) deterioration after transmitting a considerable number of messages. Interference mitigation In a complex network such as the IoT is still a subject of active research which could benefit many real-world applications. Collection trees algorithms and protocols can be used adopted to reduce the interference on the nodes/paths of an IoT network but but can not fully stop or avoid interference across an IoT network. Building upon a mapping between path interference on devices (nodes) and real life contamination of a disease that can move an individual from a susceptible (S) to infected (I) and replaced (R) statuses, this paper revisits the collection tree algorithms with the objective of studying the dynamics of the interference in IoT networks. In this study, the IoT network’s nodes are partitioned into mutually exclusive groups based on possible epidemic spread. For each group, an SIR model is proposed in a form of a system of difference equations. The model is analysed by studying the system stability and simulations are used to study the real time status of the interference across the network.