TY - JOUR
T1 - Optimal Status Update for Age of Information Minimization with an Energy Harvesting Source
AU - Wu, Xianwen
AU - Yang, Jing
AU - Wu, Jingxian
N1 - Funding Information:
Manuscript received June 20, 2017; revised October 8, 2017; accepted November 20, 2017. Date of publication November 29, 2017; date of current version March 16, 2018. This work was supported by the U.S. National Science Foundation under Grant ECCS-1405403 and Grant ECCS-1650299. This paper was presented in part at the IEEE International Conference on Communications, Paris, France, May 2017 [1]. The associate editor coordinating the review of this paper and approving it for publication was E. Ayanoglu. (Corresponding author: Jing Yang.) X. Wu is with Qualcomm CDMA Technologies Audio, Qualcomm Inc., San Diego, CA 92121 USA (e-mail: xianwenw@qti.qualcomm.com).
Publisher Copyright:
© 2017 IEEE.
PY - 2018/3
Y1 - 2018/3
N2 - In this paper, we consider a scenario where an energy harvesting sensor continuously monitors a system and sends time-stamped status updates to a destination. The destination keeps track of the system status through the received updates. We use the metric Age of Information (AoI), the time that has elapsed since the last received update was generated, to measure the 'freshness' of the status information available at the destination. Our objective is to design optimal online status update policies to minimize the long-term average AoI, subject to the energy causality constraint at the sensor. We consider three scenarios, i.e., the battery size is infinite, finite, and one unit only, respectively. For the infinite battery scenario, we adopt a best-effort uniform status update policy and show that it minimizes the long-term average AoI. For the finite battery scenario, we adopt an energy-aware adaptive status update policy, and prove that it is asymptotically optimal when the battery size goes to infinity. For the last scenario where the battery size is one, we first show that within a broadly defined class of online policies, the optimal policy should have a renewal structure. We then focus on a renewal interval, and prove that the optimal policy should have a threshold structure, i.e., if the AoI in the system is below a threshold when an energy arrival enters an empty battery, the sensor should store the energy first and then update when the AoI reaches the threshold; otherwise, it updates the status immediately. Simulation results corroborate the theoretical bounds.
AB - In this paper, we consider a scenario where an energy harvesting sensor continuously monitors a system and sends time-stamped status updates to a destination. The destination keeps track of the system status through the received updates. We use the metric Age of Information (AoI), the time that has elapsed since the last received update was generated, to measure the 'freshness' of the status information available at the destination. Our objective is to design optimal online status update policies to minimize the long-term average AoI, subject to the energy causality constraint at the sensor. We consider three scenarios, i.e., the battery size is infinite, finite, and one unit only, respectively. For the infinite battery scenario, we adopt a best-effort uniform status update policy and show that it minimizes the long-term average AoI. For the finite battery scenario, we adopt an energy-aware adaptive status update policy, and prove that it is asymptotically optimal when the battery size goes to infinity. For the last scenario where the battery size is one, we first show that within a broadly defined class of online policies, the optimal policy should have a renewal structure. We then focus on a renewal interval, and prove that the optimal policy should have a threshold structure, i.e., if the AoI in the system is below a threshold when an energy arrival enters an empty battery, the sensor should store the energy first and then update when the AoI reaches the threshold; otherwise, it updates the status immediately. Simulation results corroborate the theoretical bounds.
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U2 - 10.1109/TGCN.2017.2778501
DO - 10.1109/TGCN.2017.2778501
M3 - Article
AN - SCOPUS:85050651839
VL - 2
SP - 193
EP - 204
JO - IEEE Transactions on Green Communications and Networking
JF - IEEE Transactions on Green Communications and Networking
SN - 2473-2400
IS - 1
ER -