@inproceedings{28aaa39b7c5a42e99b00a0b8215c8b88,
title = "BIRD: Bio-inspired distributed interest forwarding in vehicular named-data networks",
abstract = "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.",
keywords = "Bio inspired, Interest forwarding, NDN, VANETs",
author = "Yaqub, {Muhammad Azfar} and Ahmed, {Syed Hassan} and Dongkyun Kim",
note = "Publisher Copyright: {\textcopyright} 2018 ACM.; 33rd Annual ACM Symposium on Applied Computing, SAC 2018 ; Conference date: 09-04-2018 Through 13-04-2018",
year = "2018",
month = apr,
day = "9",
doi = "10.1145/3167132.3167355",
language = "English",
series = "Proceedings of the ACM Symposium on Applied Computing",
publisher = "Association for Computing Machinery",
pages = "2078--2083",
booktitle = "Proceedings of the 33rd Annual ACM Symposium on Applied Computing, SAC 2018",
}