TY - GEN
T1 - Enhancements to IEEE 802.15.4 MAC Protocol to Support Vehicle-to-Roadside Communications in VANETs
AU - Khanafer, Mounib
AU - Kandil, Marwa
AU - Al-Baghdadi, Reem
AU - Al-Ajmi, Amani
AU - Mouftah, Hussein T.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - The Internet of Things (IoT) paradigm and its applications have been gaining popularity recently. The Intelligent Transportation System (ITS) is a major area of IoT applications. With ITS the transportation infrastructure is supported with advanced networking and computing technologies to better manage traffics on the roads. The Vehicular Ad-Hoc Network (VANET) stands out as an important technology under the ITS. The VANET technology supports different architectures for data communication, namely, vehicle-to-vehicle (V2V), vehicle-to-road-side (V2R), vehicle-to-infrastructure (V2I), and infrastructure-to-infrastructure (I2I). In V2R communication, data flow between vehicles and roadside units (RSUs) to convey important information about the road traffic and emergency situations. This data should be transferred with high probability of successful delivery. Also, the sensitivity of this data requires reducing the end-to-end communication delay. The IEEE 802.15.4 standard is one of the important candidate standards that supports the V2R communications. In this paper, we propose the Dynamic Window Algorithm (DWA); a backoff algorithm that targets improving the performance of V2R communications in terms of throughput and delay. This is attained by proposing changes to the operation of the standard Binary Exponent Backoff (BEB) algorithm (in IEEE 802.15.4 MAC). A Java-based simulation tool has been developed to simulate both BEB and DWA algorithms and conduct a comparison study between them. Our results show that in clusters of 20 nodes, the performance in terms of throughput and delay is improved by 32% and 88%, respectively, with DWA.
AB - The Internet of Things (IoT) paradigm and its applications have been gaining popularity recently. The Intelligent Transportation System (ITS) is a major area of IoT applications. With ITS the transportation infrastructure is supported with advanced networking and computing technologies to better manage traffics on the roads. The Vehicular Ad-Hoc Network (VANET) stands out as an important technology under the ITS. The VANET technology supports different architectures for data communication, namely, vehicle-to-vehicle (V2V), vehicle-to-road-side (V2R), vehicle-to-infrastructure (V2I), and infrastructure-to-infrastructure (I2I). In V2R communication, data flow between vehicles and roadside units (RSUs) to convey important information about the road traffic and emergency situations. This data should be transferred with high probability of successful delivery. Also, the sensitivity of this data requires reducing the end-to-end communication delay. The IEEE 802.15.4 standard is one of the important candidate standards that supports the V2R communications. In this paper, we propose the Dynamic Window Algorithm (DWA); a backoff algorithm that targets improving the performance of V2R communications in terms of throughput and delay. This is attained by proposing changes to the operation of the standard Binary Exponent Backoff (BEB) algorithm (in IEEE 802.15.4 MAC). A Java-based simulation tool has been developed to simulate both BEB and DWA algorithms and conduct a comparison study between them. Our results show that in clusters of 20 nodes, the performance in terms of throughput and delay is improved by 32% and 88%, respectively, with DWA.
UR - http://www.scopus.com/inward/record.url?scp=85070215089&partnerID=8YFLogxK
U2 - 10.1109/ICC.2019.8761245
DO - 10.1109/ICC.2019.8761245
M3 - Conference contribution
AN - SCOPUS:85070215089
T3 - IEEE International Conference on Communications
BT - 2019 IEEE International Conference on Communications, ICC 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Communications, ICC 2019
Y2 - 20 May 2019 through 24 May 2019
ER -