Controlling Actor Mobility in Wireless Sensor and Actor Networks

Mobile actors are efficient devices for wireless sensor and actor networks especially in mission critical environments. With controlling the mobility of actors efficiency of network can beincreased. Location service is an efficient approach for actor mobility control. Mls is one of the proposed works which benefits from location service. Mls shares its strategy model in update packets in order to improve the performance of location service. The mobility model used in thisprotocol is random waypoint mobility which actor moves randomly around the network. In this paper, we propose a Q-learning based sharing mobility location service protocol called Qmls, replacing the mobility model of mls with intelligent one called ORACLE. In this mobility model actor chooses the next waypoint with awareness to become closer to event area. Simulation results show the effectiveness of our work.

Controlling Actor Mobility in Wireless Sensor and Actor Networks Keywords:

wireless sensor and actor networks , mobility control , Location service , markov decision process , Q-learning