%0 Conference Paper %1 leh20ITC32 %A Wang, Lehan %A Sun, Jingzhou %A Zhou, Sheng %A Niu, Zhisheng %B 32th International Teletraffic Congress (ITC 32) %C Osaka, Japan %D 2020 %K itc itc32 %T Timely Status Update Based on Urgency of Information with Statistical Context %U https://gitlab2.informatik.uni-wuerzburg.de/itc-conference/itc-conference-public/-/raw/master/itc32/leh20ITC32.pdf?inline=true %X Real-time status update has recently brought the widespread attentions, especially in the field of remote control. Accordingly, a metric named Urgency of Information (UoI) has been proposed to capture the timeliness of information and the evolution of the context at the same time. It is defined as the product of the context-aware weight and the cost function of the estimation error. However, the metric itself does not indicate how to determine the contextual weight. Based on UoI, this paper proposes a dynamic threshold-based scheduling policy which only requires the conditional expectation of the weight in the next time slot by Lyapunov method. When the environment is unknown, We also use the online algorithm SARSA to obtain a policy. The simulation results show that both policies are near-optimal when the update resources are relatively rich, and the SARSA-based policy works better under the tight resources constraint over the Lyapunov method.

@inproceedings{leh20ITC32, abstract = {Real-time status update has recently brought the widespread attentions, especially in the field of remote control. Accordingly, a metric named Urgency of Information (UoI) has been proposed to capture the timeliness of information and the evolution of the context at the same time. It is defined as the product of the context-aware weight and the cost function of the estimation error. However, the metric itself does not indicate how to determine the contextual weight. Based on UoI, this paper proposes a dynamic threshold-based scheduling policy which only requires the conditional expectation of the weight in the next time slot by Lyapunov method. When the environment is unknown, We also use the online algorithm SARSA to obtain a policy. The simulation results show that both policies are near-optimal when the update resources are relatively rich, and the SARSA-based policy works better under the tight resources constraint over the Lyapunov method.}, added-at = {2021-03-02T15:22:25.000+0100}, address = {Osaka, Japan}, author = {Wang, Lehan and Sun, Jingzhou and Zhou, Sheng and Niu, Zhisheng}, biburl = {https://www.bibsonomy.org/bibtex/2fcc5586e31b311757596c9636850d2c9/itc}, booktitle = {32th International Teletraffic Congress (ITC 32)}, interhash = {0b0f703f5a0b426c4c89045c82e5d272}, intrahash = {fcc5586e31b311757596c9636850d2c9}, keywords = {itc itc32}, timestamp = {2021-03-02T15:22:25.000+0100}, title = {Timely Status Update Based on Urgency of Information with Statistical Context}, url = {https://gitlab2.informatik.uni-wuerzburg.de/itc-conference/itc-conference-public/-/raw/master/itc32/leh20ITC32.pdf?inline=true}, year = 2020 }