TY - GEN
T1 - Age-minimal online policies for energy harvesting sensors with random battery recharges
AU - Arafa, Ahmed
AU - Yang, Jing
AU - Ulukus, Sennur
N1 - Funding Information:
This research was supported in part by the National Science Foundation under Grants ECCS-1650299, CCF 14-22111, and CNS 15-26608.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/27
Y1 - 2018/7/27
N2 - We consider an energy harvesting sensor that is sending measurement updates regarding some physical phenomenon to a destination. The sensor relies on energy harvested from nature to measure and send its updates, and is equipped with a battery of finite size to collect its harvested energy. The energy harvesting process is Poisson with unit rate, and arrives in amounts that fully recharge the battery. Our setting is online in the sense that the times of energy arrivals are revealed causally to the sensor after the energy is harvested; only the statistics of the arrival process is known a priori. Updates need to be sent in a timely manner to the destination, namely, such that the long term average age of information is minimized over the course of communication. The age of information is defined as the time elapsed since the freshest update has reached the destination. We first show that the optimal scheduling update policy is a renewal policy, and then show that it has a multi threshold structure: the sensor sends an update only if the age of information grows above a certain threshold that depends on the available energy.
AB - We consider an energy harvesting sensor that is sending measurement updates regarding some physical phenomenon to a destination. The sensor relies on energy harvested from nature to measure and send its updates, and is equipped with a battery of finite size to collect its harvested energy. The energy harvesting process is Poisson with unit rate, and arrives in amounts that fully recharge the battery. Our setting is online in the sense that the times of energy arrivals are revealed causally to the sensor after the energy is harvested; only the statistics of the arrival process is known a priori. Updates need to be sent in a timely manner to the destination, namely, such that the long term average age of information is minimized over the course of communication. The age of information is defined as the time elapsed since the freshest update has reached the destination. We first show that the optimal scheduling update policy is a renewal policy, and then show that it has a multi threshold structure: the sensor sends an update only if the age of information grows above a certain threshold that depends on the available energy.
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U2 - 10.1109/ICC.2018.8422086
DO - 10.1109/ICC.2018.8422086
M3 - Conference contribution
AN - SCOPUS:85050695137
SN - 9781538631805
T3 - IEEE International Conference on Communications
BT - 2018 IEEE International Conference on Communications, ICC 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Communications, ICC 2018
Y2 - 20 May 2018 through 24 May 2018
ER -