Information theory based performance analysis and enhancement of Safety applications and cluster design in VANET

Abstract

Safety applications in vehicular ad hoc network (VANET) are handled by broadcast to disseminate safety related messages, due to lack of stable topology. The mobility of vehicles leads to significant performance degradation, especially in dense and dynamic scenarios. This paper presents an information theory based mobility model to determine the theoretical amount of information for VANET safety applications. The new mobility model considers the safety distance and vehicle's status. Analysis results are helpful in reducing redundant information and gaining more insight for system design. Based on the model, an adaptive algorithm to derive the optimal data rate is proposed. In addition, an adaptive control channel interval (CCI) algorithm is applied in cluster forming to improve stability of cluster topology. Numerical simulations based on NS-3 show that algorithms proposed can improve the performance dramatically, and the effectiveness of the safety requirements is guaranteed.

Performance Analysis of DCT Based Lossy Compression Method with Symmetrical Encryption Algorithms

“…The proposed method is applied on six gray scale images having different sizes and it also shows that the reconstructed images are efficient and having high quality. Performance Analysis of DCT Based Lossy Compression Method with Symmetrical Encryption Algorithms 3 Shen H., L. Zhang et al [18] have proposed an burgeoning compressive sensing based baysian dictionary learning algorithm. Authors have used this algorithm to overcome the problem of dead pixel strips in MODIS.…”