TY - GEN
T1 - Performance Evaluation of Probabilistic Broadcast in Low-Power and Lossy Networks
AU - Ali-Fedila, Djahida
AU - Ould-Khaoua, Mohamed
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - 6LowPAN
KW - Flooding
KW - IEEE 802.15.4
KW - IoT
KW - LLNs
KW - Performance Evaluation
KW - Probabilistic Broadcast
KW - Simulations
UR - http://www.scopus.com/inward/record.url?scp=85127662270&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85127662270&partnerID=8YFLogxK
U2 - 10.1109/IUCC-CIT-DSCI-SmartCNS55181.2021.00049
DO - 10.1109/IUCC-CIT-DSCI-SmartCNS55181.2021.00049
M3 - Conference contribution
AN - SCOPUS:85127662270
T3 - Proceedings - 2021 20th International Conference on Ubiquitous Computing and Communications, 2021 20th International Conference on Computer and Information Technology, 2021 4th International Conference on Data Science and Computational Intelligence and 2021 11th International Conference on Smart Computing, Networking, and Services, IUCC/CIT/DSCI/SmartCNS 2021
SP - 247
EP - 254
BT - Proceedings - 2021 20th International Conference on Ubiquitous Computing and Communications, 2021 20th International Conference on Computer and Information Technology, 2021 4th International Conference on Data Science and Computational Intelligence and 2021 11th International Conference on Smart Computing, Networking, and Services, IUCC/CIT/DSCI/SmartCNS 2021
A2 - Hu, Jia
A2 - Hao, Fei
A2 - Wang, Haozhe
A2 - Wang, Miaoqiong
A2 - Zhang, Xu
A2 - Zhao, Zhiwei
A2 - Wang, Zi
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th International Conference on Ubiquitous Computing and Communications, 20th International Conference on Computer and Information Technology, 4th International Conference on Data Science and Computational Intelligence and 11th International Conference on Smart Computing, Networking, and Services, IUCC/CIT/DSCI/SmartCNS 2021
Y2 - 20 December 2021 through 22 December 2021
ER -