Modeling and evaluation of RPL routing protocol by colored Petri nets

The Internet of Things (IoT) is a novel and widely used idea aimed at connecting objects through communication technologies. The problem of the prior technology adaptation has always been one of the most challenging issues in this area over the years. The Recognition of Prior Learning (RPL) protocol has been proposed by scientists since 2012 as a solution for IoT routing. This protocol has been utilized by many researchers and hardware companies in the field of the mentioned technology. The present study evaluates RPL behavior from the perspective of the existence of stopping conditions, crossing multiple routes from a special route (loop conditions), and how it reacts to different inputs, while presenting a modular and readable model of this protocol.