Leveraging Content Connectivity and Location Awareness for Adaptive Forwarding in NDN-based Mobile Ad Hoc Networks


Communication in Mobile Ad-hoc Networks (MANETs) is challenging due to their highly dynamic topology, intermittent connectivity, and low data rate. Named Data Networking (NDN) offers a data-centric approach to communication with an adaptive forwarding plane and in-network data caching, which can be leveraged to address these challenges. In this work, we propose a forwarding strategy called Content Connectivity and Location-Aware Forwarding (CCLF) for NDN-based MANETs. CCLF broadcasts NDN packets and lets each node make independent decisions on whether to forward packets based on per-prefix performance measurements and any available geo-location information. In addition, it employs a density-aware suppression mechanism to reduce unnecessary packet transmissions. Moreover, we have developed a link adaptation layer for ad-hoc links to bridge the gap between CCLF and the capabilities of the underlying link. Our evaluation shows that CCLF not only reduces packet overhead significantly compared to flooding, but also has a data fetching performance close to that achieved by flooding. It also outperforms three other forwarding strategies proposed for information-centric vehicular networks.

Publication Title

ICN 2020 - Proceedings of the 7th ACM Conference on Information-Centric Networking