TY - GEN
T1 - Online Timely Status Updates with Erasures for Energy Harvesting Sensors
AU - Arafa, Ahmed
AU - Yang, Jing
AU - Ulukus, Sennur
AU - Poor, H. Vincent
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - An energy harvesting sensor that is sending status updates to a destination through an erasure channel is considered, in which transmissions are prone to being erased with some probability q, independently from other transmissions. The sensor, however, is unaware of erasure events due to lack of feedback from the destination. Energy expenditure is normalized in the sense that one transmission consumes one unit of energy. The sensor is equipped with a unit-sized battery to save its incoming energy, which arrives according to a Poisson process of unit rate. The setting is online, in which energy arrival times are only revealed causally after being harvested, and the goal is to design transmission times such that the long term average age of information (AoI), defined as the time elapsed since the latest update has reached the destination successfully, is minimized. The optimal status update policy is first shown to have a renewal structure, in which the time instants at which the destination receives an update successfully constitute a renewal process. Then, for q\leq \frac {1}{2}, the optimal renewal policy is shown to have a threshold structure, in which a new status update is transmitted only if the AoI grows above a certain threshold, that is shown to be a decreasing function of q. While for q \gt \frac {1}{2}, the optimal renewal policy is shown to be greedy, in which a new status update is transmitted whenever energy is available.
AB - An energy harvesting sensor that is sending status updates to a destination through an erasure channel is considered, in which transmissions are prone to being erased with some probability q, independently from other transmissions. The sensor, however, is unaware of erasure events due to lack of feedback from the destination. Energy expenditure is normalized in the sense that one transmission consumes one unit of energy. The sensor is equipped with a unit-sized battery to save its incoming energy, which arrives according to a Poisson process of unit rate. The setting is online, in which energy arrival times are only revealed causally after being harvested, and the goal is to design transmission times such that the long term average age of information (AoI), defined as the time elapsed since the latest update has reached the destination successfully, is minimized. The optimal status update policy is first shown to have a renewal structure, in which the time instants at which the destination receives an update successfully constitute a renewal process. Then, for q\leq \frac {1}{2}, the optimal renewal policy is shown to have a threshold structure, in which a new status update is transmitted only if the AoI grows above a certain threshold, that is shown to be a decreasing function of q. While for q \gt \frac {1}{2}, the optimal renewal policy is shown to be greedy, in which a new status update is transmitted whenever energy is available.
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U2 - 10.1109/ALLERTON.2018.8636088
DO - 10.1109/ALLERTON.2018.8636088
M3 - Conference contribution
AN - SCOPUS:85062856153
T3 - 2018 56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018
SP - 966
EP - 972
BT - 2018 56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018
Y2 - 2 October 2018 through 5 October 2018
ER -