Navigation Route Based Stable Clustering for Vehicular Ad Hoc Networks

Due to high node mobility, stability has been always one of the major concerns of vehicle clustering algorithms in vehicular ad hoc networks. In this paper, we propose a novel clustering algorithm based on the information of routes planned by vehicular navigation systems. In the clustering algorithm, we design a residual route time function to quantitatively calculate the overlapping time among vehicles based on route information, with which a novel clusterhead selection metric is presented. We further design a mechanism of future-clusterhead, which can help avoid message exchanges at intersections and reduce the overhead of cluster maintenance. The simulation results show that, compared with previous works, our clustering algorithm can achieve higher stability and at the same time lower communication cost.

A Novel DSA-Driven MAC Protocol for Cognitive Radio Networks

With the deployment of more wireless applications, spectrum scarcity becomes an issue in many countries. Recent reports show that the reason for this spectrum shortage is the underutilization of some spectrum re-sources. Fortunately, the emergence of open spectrum and dynamic spectrum assess (DSA) technology in cognitive radio networks relieves this problem. In this paper, we propose a novel DSA-driven cognitive MAC protocol to achieve highly efficient spectrum usage and QoS provisioning. In the proposed protocol, secondary users are divided into several non-overlapping groups, and all leftover channels are allocated among groups taking the groups’ bandwidth requirements into consideration. Moreover, the allocation of vacant channels can be adjusted dynamically when members join/leave groups or primary users return/leave the current network. Simulations show that the proposed MAC protocol greatly improves the quality of ser-vice for secondary users and maximizes the utilization ratio of spectrum resources.