Optimizing Broadcasting Scheme for VANETs Using Genetic Algorithm

Broadcasting is one of the communication mechanism utilised in VANET architecture through which an up-to-date traffic data can be disseminated among the commuters and this can help reduce traffic jams/congestions. Broadcasting storm (broadcasting) is considered to be an NP-hard problem consisting of multiple objectives. Conventional techniques use Multi-Objective Genetic Algorithms (MOGAs) to solve such optimization problems. Performance of such algorithms depend on fitness function. In this paper, we propose a novel and improved fitness function for MOGA to solve the broadcasting problem in VANETs. The proposed fitness function has enhanced the rate of evolution, resulting in more generations and producing better optimization results. We consider a highway scenario for simulation to evaluate performance of the proposed solutions. We compare the results of the proposed algorithm with existing state-of-the-art technique [1]. Our results show improvement in reduction of the propagation time and the number of retransmissions compared to the previous solution.