Wei Chen

TL;DR: This paper model an unsaturated VANET cluster with a Markov chain by introducing an idle state and reveals intrinsic dependencies between cluster size, vehicle speed, traffic demand, and window size, as well as their impacts on the overall throughput and packet loss of the cluster.

TL;DR: This work presents an SDN-based UASN framework, followed by the design of a clustering method in which learning automata and degree-constrained connected dominating sets are employed, and proposes a load balancing mechanism involving multiple controllers, based on the consistent hashing algorithm.

TL;DR: The research results emphasize the significance of the V2V radio channel modeling under ramp scenarios, demonstrating the difference of path loss values in the transition region owing to the impact of soundproof walls.

TL;DR: A comprehensive review on the advances in software-defined UASNs and the progress of the Software-Defined Radio (SDR), Cognitive Radio (CR), and SDN is provided.

TL;DR: In this paper, a propagation path loss model for inland river is proposed by three improvements compared with the Round Earth Loss (REL) model for open-sea environment, which uses Okumura-Hata model in dB scale to replace the equation transformed from the free space loss in REL model; secondly, diffraction loss caused by the obstacles (e.g., large buildings, bridges, or some other facilities near the river bank) is also taken into account; mixed-path methodology as another improvement is used for Inland River (IR) model because the actual propagation environment between