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

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In this article, the authors considered an energy-harvesting sensor node that is sending status updates to a destination, and the goal is to design status update transmission times (policy) such that the long term average AoI is minimized.
Abstract: 
An energy-harvesting sensor node that is sending status updates to a destination is considered. The sensor is equipped with a battery of finite size to save its incoming energy, and consumes one unit of energy per status update transmission, which is delivered to the destination instantly over an error-free channel. The setting is online in which the harvested energy is revealed to the sensor causally over time after it arrives, and the goal is to design status update transmission times (policy) such that the long term average age of information (AoI) is minimized. The AoI is defined as the time elapsed since the latest update has reached at the destination. Two energy arrival models are considered: a random battery recharge (RBR) model, and an incremental battery recharge (IBR) model. In both models, energy arrives according to a Poisson process with unit rate, with values that completely fill up the battery in the RBR model, and with values that fill up the battery incrementally in a unit-by-unit fashion in the IBR model. The key approach to characterizing the optimal status update policy for both models is showing the optimality of renewal policies , in which the inter-update times follow a renewal process in a certain manner that depends on the energy arrival model and the battery size. It is then shown that the optimal renewal policy has an energy-dependent threshold structure, in which the sensor sends a status update only if the AoI grows above a certain threshold that depends on the energy available in its battery. For both the random and the incremental battery recharge models, the optimal energy-dependent thresholds are characterized explicitly , i.e., in closed-form, in terms of the optimal long term average AoI. It is also shown that the optimal thresholds are monotonically decreasing in the energy available in the battery, and that the smallest threshold, which comes in effect when the battery is full, is equal to the optimal long term average AoI.

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Journal ArticleDOI

The Age of Information: Real-Time Status Updating by Multiple Sources

TL;DR: An age of information timeliness metric is formulated and a general result for the AoI that is applicable to a wide variety of multiple source service systems is derived that makes AoI evaluation to be comparable in complexity to finding the stationary distribution of a finite-state Markov chain.
Posted Content

Age of Information: An Introduction and Survey

TL;DR: The current state of the art in the design and optimization of low-latency cyberphysical systems and applications in which sources send time-stamped status updates to interested recipients is described and AoI timeliness metrics are described.
Journal ArticleDOI

Age of Information: An Introduction and Survey

TL;DR: In this paper, the authors summarize recent contributions in the broad area of AoI and present general AoI evaluation analysis that are applicable to a wide variety of sources and systems, starting from elementary single-server queues, and applying these AoI methods to a range of increasingly complex systems, including energy harvesting sensors transmitting over noisy channels, parallel server systems, queueing networks, and various single-hop and multi-hop wireless networks.
Journal ArticleDOI

Timely Status Update in Internet of Things Monitoring Systems: An Age-Energy Tradeoff

TL;DR: Simulations validate the theoretical analysis and reveal that under the same average transmit power constraint, the adopted TARQ scheme achieves a lower average AoI than the classical ARQ scheme that allows an infinite number of retransmission times.
Book

Age of Information: A New Metric for Information Freshness

TL;DR: Abstract Information usually has the highest value when it is fresh, and for example, real-time knowledge about the location, orientation, and speed of motor vehicles is imperative in autonomous vehicles.
References
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Stochastic Processes

Journal ArticleDOI

On Nonlinear Fractional Programming

TL;DR: In this paper, an algorithm for fractional programming with nonlinear as well as linear terms in the numerator and denominator is presented. But the algorithm is based on a theorem by Jagannathan Jagannathy, R. 1966.
Proceedings ArticleDOI

Real-time status: How often should one update?

TL;DR: A time-average age metric is employed for the performance evaluation of status update systems and the existence of an optimal rate at which a source must generate its information to keep its status as timely as possible at all its monitors is shown.
Journal ArticleDOI

Transmission with Energy Harvesting Nodes in Fading Wireless Channels: Optimal Policies

TL;DR: In this paper, the authors consider a point-to-point data transmission with an energy harvesting transmitter which has a limited battery capacity, communicating in a wireless fading channel, and they consider two objectives: maximizing the throughput by a deadline, and minimizing the transmission completion time of the communication session.
Posted Content

Transmission with Energy Harvesting Nodes in Fading Wireless Channels: Optimal Policies

TL;DR: This paper considers optimization of point-to-point data transmission with an energy harvesting transmitter which has a limited battery capacity, communicating in a wireless fading channel, and introduces a directional water-filling algorithm which provides a simple and concise interpretation of the necessary optimality conditions.
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