Performance Evaluation of Probabilistic Broadcast in Low-Power and Lossy Networks
Djahida Ali-Fedila, Mohamed Ould‐Khaoua · 2021
This study investigates the suitability of probabilistic broadcast for Low-power and Lossy Networks (LLNs) based IoT networks with IPV6 and 6lowPAN support, taking into account the constrained capabilities of the latter in terms of processing power, storage, battery power, and lossy links. To the best of our knowledge, our research is among the first to investigate the performance merits of probabilistic broadcast in the context of LLNs which are expected to be the backbone of numerous practical IoT deployments. The performance of probabilistic broadcast is compared against well-known state-of-the-art broadcast protocols for LLNs including Trickle-based Broadcast (TM), Stateless Multicast RPL Forwarding (SMRF), and Blind Flooding (FLOOD) for both static and mobile environments. Our performance results reveal that through a careful selection of the forwarding probability, in our case it has been found to approximately 0.5, probabilistic broadcast can noticeably outperform the existing FLOOD, TM and SMRF in terms of important performance metrics including reachability and number of retransmissions.