Parallel Swarm Intelligence for VANETs Optimization

Parallel metaheuristics can enhance and speed up the resolution of hard-to-solve optimization problems by taking advantage of the available processing power. in this study, we present a parallel swarm intelligent method, pPSO, that uses the master-slave paradigm to evaluate all the particles simultaneously over several processing elements.

We have applied pPSO to tackle the AODV routing optimization in VANETs, a problem that requires large computation times to evaluate the fitness function. in turn, we apply parallelism for the comprehensive validation of solutions in the simulation analysis. the AODV configuration optimized by pPSO shows the best trade-off among several QoS metrics when compared against state of the art configurations. Our pPSO achieved an average computational efficiency of 86%.

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