Performance Evaluation of Probabilistic Interest Forwarding in NDN over LLNs
Adel Salah Ould Khaoua, Abdelmadjid Boukra, Fella Bey · 2022
This study investigates the merits of adopting probabilistic interest forwarding in Named Data Networks (NDN) deployed over IEEE 802.15.4 communication technologies, which are also known as Low-power & Lossy Networks (LLNs), considering their limited capabilities including computation, energy, and communication. To this end, we evaluate the performance of probabilistic forwarding and compared it against that of Deferred Blind Flooding (DBF) which is one of the most widely used strategies for interest forwarding in NDN. Our performance results reveal that probabilistic forwarding exhibits superior performance over DBF with respect to important performance measures such as number of sent packets and latency while achieving high interest satisfaction rates.