Abstract-Data Collection is considered as an inherent challenging problem to Vehicular Ad-Hoc networks. Here, an Adaptive Data cOllection Protocol using rEinforcement Learning (ADOPEL) is proposed for VANETs. It is based on a distributed Qlearning technique making the collecting operation more reactive to nodes mobility and topology changes. A reward function is provided and defined to take into account the delay and the number of aggregatable packets. Simulations results confirm the efficiency of our technique compared to a non-learning version and demonstrate the trade-off achieved between delay and collection ratio.
Soua et al. proposed ADOPEL protocol based on a distributed Q learning techniqueto make the collecting operation more reactive to nodes mobility and topology changes REF .
Adaptive data collection protocol using reinforcement learning for VANETs
2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC)
2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC)
Computer Science