Date of Award
Master of Science
Intelligent Transport System (ITS) applications rely on efficient forwarding or routing ofthe packet. However, routing or forwarding packet in Connected Vehicles is a challenging task and data retrieval rate can be very low due to highly dynamic topology andintermittent connectivity. Most of the routing solutions in the literature are location-based accompanied with limited flooding when location information is not available. For efficient communication and data retrieval in the vehicular network, we propose a hybrid forwarding solution, called CCLF. CCLF takes into account content-based connectivity information, i.e., Interest satisfaction ratio for each name prefix, in its forwarding decisions. To overcome the shortcomings of IP in mobile environment, CCLF is based ona data-centric network called Named Data Network (NDN). By keeping track of content connectivity and giving higher priority to vehicles with better content connectivity to forward Interests, CCLF not only reduces Interest flooding when location information is unknown or inaccurate, but also increases data fetching rate.
dissertation or thesis originally submitted to the local University of Memphis Electronic Theses & dissertation (ETD) Repository.
Chowdhury, Muktadir Rahman, "A Smart Forwarding in NDN VANET" (2019). Electronic Theses and Dissertations. 2046.