So much interest has been drawn to producing more devices that will constitute the Internet of Things (IoT), however, the means to organize these devices into a network of things has remained a grey area. With the bulk of the emphasis channeled towards proliferating the number of embedded systems to compensate their growing demand, designing different IoT concepts and applications, and also prototyping different wireless sensor networks, a little concern has been directed to the study of quality of service relative to the exploding amount of data expected in the IoT network.

In a typical IoT-based Smart Home Network, just as in our case, a ZigBee network, end devices send an enormous amount of data to the coordinator and other end devices through intermediary devices like routers. This, as a result, creates overhead application traffic in the coordinator’s queue. The built-up queue causes congestion and subsequent dropping of packets, increasing delay and reducing throughput. Therefore, it becomes imperative to develop an operative active queue model that will ensure quick and reliable data mobility within or by across multiple Personal Area Networks (PAN).

This work investigates a power-efficient ZigBee-enabled Smart Home Network that employs the Random Early Detection-Active Queue Management (RED-AQM) model to provide reliable data transport in the Smart Home context. We focus on the simulation of different network topologies for single and multiple PANs and identify the optimal network setup when using RED-AQM.

Keywords

Random Early Detection, Internet of Things, ZigBee, Personal Area Networks, Queuing