BIRD: Bio-Inspired Distributed Interest Forwarding in Vehicular Named-Data Networks
Contribution to Book
Proceedings of the Association for Computing Machinery Symposium on Applied Computing
In this work we tackle the problem of congestion and Interest broadcast storm problem in vehicular named data networks (VNDN) and propose a bio-inspired approach which makes the Interest forwarding self-adaptive and autonomous. The properties like scalability, self-adaptiveness, and simplicity are inherently available to the biological species. These properties are desirable in the VNDN environment, who face the daunting issue of Interest flooding and congestion. The proposed Bio-Inspired Distributed (BIRD) Interest forwarding scheme allows the on-road vehicles to make intelligent Interest forwarding decisions based on the simple rules followed birds in nature. The Interest packets are guided through multiple paths in a flock like manner towards the provider. Simulation results show that at the cost of additional packets for multiple paths we achieve an average of 20% higher Content satisfaction ratio from both RUFS and NAIF. Additionally, BIRD incurs 10% less delay as compared to the multi-path NIAF scheme in urban scenarios with varying network density.
Yaqub, Muhammad Azfar, Syed Hassan Ahmed, Dongkyun Kim.
"BIRD: Bio-Inspired Distributed Interest Forwarding in Vehicular Named-Data Networks."
Proceedings of the Association for Computing Machinery Symposium on Applied Computing: 2078-2083 New York, NY: Association for Computing Machinery.
doi: 10.1145/3167132.3167355 source: https://dl.acm.org/citation.cfm?doid=3167132.3167355 isbn: 978-1-4503-5191-1