For different network traffic and network state’s time-varying characteristics, this paper studies the highly energy-efficient network selection algorithm under dynamic change. Network selection algorithm has an important impact on network… Click to show full abstract
For different network traffic and network state’s time-varying characteristics, this paper studies the highly energy-efficient network selection algorithm under dynamic change. Network selection algorithm has an important impact on network performance and users’ experience, while current network selection schemes depend on a prior. They cannot effectively select the appropriate network. Targeting users’ quality of experience (QoE) and networks’ energy consumption, this paper uses online dynamic learning property of Q-learning method, consider users’ QoE, networks’ energy consumption, and switch times together, and proposes a QoE based dynamic network selection algorithm. This algorithm can dynamically select the network, obtain the maximum users’ QoE and optimize networks’ energy consumption and switch times. Simulation results show that the proposed algorithm exhibits better performance.
               
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