Izvorni znanstveni članak
https://doi.org/10.1080/00051144.2019.1592290
Dynamic speed adaptive classified (D-SAC) data dissemination protocol for improving autonomous robot performance in VANETs
M. Vijayaraj
; Department of Information Technology, Mohamed Sathak Engineering College, Ramanathapuram, India
S. Srinivasan
; Computer Science and Engineering, Regional Centre of Anna University Madurai, Madurai, India
Sažetak
In robotics, mechanized and computer simulation for accurate and fast crash detection between general geometric models is a fundamental problem. The explanation of this problem will gravely improve driver safety and traffic efficiency, vehicular ad hoc networks (VANETs) have been employed in many scenarios to provide road safety and for convenient travel of the people. They offer self-organizing decentralized environments to disseminate traffic data, vehicle information and hazardous events. In order to avoid accidents during roadway travels, which are a major burden to the society, the data, such as traffic data, vehicle data and the road condition, play a critical role. VANET is employed for disseminating the data. Still the scalability issues occur when the communication happens under high-traffic regime where the vehicle density is high. The data redundancy and packet collisions may be high which cause broadcast storm problems. Here the traffic regime in the current state is obtained from the speed of the vehicle. Thus the data reduction is obtained. In order to suppress the redundant broadcast D-SAC data, dissemination protocol is presented in this paper. Here the data are classified according to its criticality and the probability is determined. The performance of the D-SAC protocol is verified through conventional methods with simulation.
Ključne riječi
Robotics; VANETs; broadcast storm; probabilistic approach; dynamic speed adaptive classified (D-SAC) data dissemination protocol; data classification; critical data; non-critical data
Hrčak ID:
239840
URI
Datum izdavanja:
31.10.2019.
Posjeta: 667 *