Energy Optimization for Mobile Applications by Exploiting 5G Inactive State

The high energy consumption of 5G New Radio (NR) poses a major challenge to user experience. A major source of energy consumption in User Equipments (UE) is the radio tail, during which the UE remains in a high-power state to release the radio sources. Existing energy optimization approaches cut radio tails by forcing the UE to enter a low-power state. However, these approaches introduce extra promotion delays and energy consumption with soon-coming data transmissions. In this paper, we first conduct an empirical study to reveal that the 5G radio tail introduces significant energy waste on UEs. Then we propose 5GSaver, a two-phase energy-saving approach that utilizes the inactive state of New Radio to better eliminate the tail in 5G cellular networks. 5GSaver identifies the end of App communication events in the first phase and predicts the next packet arrival time in the second phase. With the learning results, 5GSaver can automatically help the UE determine which radio resource control state to enter for saving energy. We evaluate 5GSaver using 15 mobile Apps on commercial smartphones. Evaluation results show that 5GSaver can reduce radio energy consumption by 9.5% and communication delay by 12.4% on average compared to the state-of-the-art approach.