Using Erasure Feedback for Online Timely Updating with an Energy Harvesting Sensor

Abstract

A real-time status updating system is considered, in which an energy harvesting sensor is acquiring measurements regarding some physical phenomenon and sending them to a destination through an erasure channel. The setting is online, in which energy arrives in units according to a Poisson process with unit rate, with arrival times being revealed causally over time. Energy is saved in a unit-sized battery. The sensor is notified by the destination of whether updates were erased via feedback. Updates need to reach the destination successfully in a timely fashion, namely, such that the long term average age of information, defined as the time elapsed since the latest successful update has reached the destination, is minimized. First, it is shown that the optimal status update policy has a renewal structure: successful update times should constitute a renewal process. Then, threshold-greedy policies are investigated: a new update is transmitted, following a successful one, only if the age of information grows above a certain threshold; and if it is erased, then all subsequent update attempts are greedily scheduled whenever energy is available. The optimal thresholdgreedy policy is then analytically derived.

Age-Minimal Transmission for Energy Harvesting Sensors With Finite Batteries: Online Policies

“…One extension is to study the problem in which updates are subject to erasures, and show how threshold policies behave under such setting. We note that an effort toward that has been made for the setting in which the sensor is equipped with a unit-sized battery in [56,57], where erasure-dependent threshold policies are shown to be age-minimal. Another extension would be to combine both recharging models studied in this paper in one setting where energy also arrives according to a Poisson process, yet with value e ∈ {1, 2, .…”

Trading Off Computation with Transmission in Status Update Systems

“…[3], [4] investigate the role of packet management to decrease the AoI while [5] provides a general AoI analysis in various preemptive and non-preemptive queuing disciplines coming after earlier works such as [6], [7]. References [8]- [17] consider AoI in energy harvesting communication systems. Evolution of AoI through multiple hops in networks have been characterized in [18]- [22] and [23]- [25] consider AoI minimization over multiple access and broadcast channels.…”

AoI Minimization in Status Update Control With Energy Harvesting Sensors

“…We consider an error-free binary/single-bit command link from the edge node to each sensor [21], [32], and an error-prone wireless communication link from each sensor to the edge node, as illustrated in Fig. 2.…”

“…In [20], the authors derived age-optimal online policies for an EH sensor having a unit-sized or infinite battery using renewal theory. In [21], the authors explored the benefits of erasure status feedback for online timely updating for an EH sensor with a unit-sized battery. Age-optimal transmission policies for EH two-hop networks were investigated in [22].…”