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Cluster‐based emergency message dissemination strategy for VANET using V2V communication
Author(s) -
Benkerdagh Saliha,
Duvallet Claude
Publication year - 2019
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.3897
Subject(s) - computer science , vehicular ad hoc network , computer network , dissemination , network packet , reliability (semiconductor) , quality of service , bandwidth (computing) , wireless ad hoc network , distributed computing , heuristic , wireless , telecommunications , power (physics) , physics , quantum mechanics , artificial intelligence
Summary Data dissemination in vehicular ad hoc network (VANET) is emerging as a critical area of research. One of the challenges posed by this domain is the reliability of connection, which depends on many parameters, such as the bandwidth consumption, transmission delay, and data quality of service (QoS). Dissemination of emergency messages is very critical since the network topology is changing frequently and rapidly, which leads to data loss. So, it is necessary to develop new protocols and enhance dissemination schemes in VANET to avoid more emergencies and hazards cases. In this regard, we have proposed a new strategy, which consists of data handling before dissemination process as the first step of our scheme. In this phase, the original message is optimized in order to reduce the number of exchanged packets. The second part of this proposition consists of constructing fast and stable clusters to improve the message delivery time and to procure efficient bandwidth consumption. This approach is based on a F i t n e s s function, which takes into account different parameters such as the transmission period, the connectivity degree, the relative velocity, and the link lifetime validity. Since exchanging data in VANET is an important process, routing phase is proposed to perform data exchange among clusters. It is based on a rapid and real‐time heuristic (real‐time adaptive A* [RTAA*]). To evaluate the reliability of the proposed approach, an urban scenario is used with different simulation parameters. The simulation results show that our proposed approach presents a better stability and efficiency performance compared with the discussed approaches. The proposed approach improves the performance of cluster duration (5 % − 25 % ), delivery rate (2 % − 8 % ), and the overhead (5 % − 35 % ) on average compared with the discussed approaches.