Unifying AoI Minimization and Remote Estimation—Optimal Sensor/Controller Coordination With Random Two-Way Delay

Tsai, Cho-Hsin; Wang, Chih-Chun

doi:10.1109/tnet.2021.3111495

Cited by 25 publications

(11 citation statements)

References 24 publications

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“…Nowadays, AoI is widely used in many applications including sensors, control and vehicular networks since AoI measures the quality of information in terms of timeliness [2]- [6]. Given random arrival and delivery of new status, [7]- [13] have characterized AoI in different types of channels: non-shared independent channels [7], [8], broadcasting channels [9], [10], and random access channel [11]- [13].…”

mentioning

confidence: 99%

Optimal Scheduling Policy for Minimizing Age of Information with a Relay

Song,

Gunduz,

Choi

2020

Preprint

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We consider IoT sensor network where multiple sensors are connected to corresponding destination nodes via a relay. Thus, the relay schedules sensors to sample and destination nodes to update. The relay can select multiple sensors and destination nodes in each time. In order to minimize average weighted sum AoI, joint optimization of sampling and updating policy of the relay is investigated. For errorless and symmetric case where weights are equally given, necessary and sufficient conditions for optimality is found. Using this result, we obtain that the minimum average sum AoI in a closed-form expression which can be interpreted as fundamental limit of sum AoI in a single relay network. Also, for error-prone and symmetric case, we have proved that greedy policy achieves the minimum average sum AoI at the destination nodes. For general case, we have proposed scheduling policy obtained via reinforcement learning.

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confidence: 99%

Optimal Scheduling Policy for Minimizing Age of Information with a Relay

Song,

Gunduz,

Choi

2020

Preprint

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“…An optimal online scheduling in the presence of random delays is developed in [30], whereas we study a predefined (hence offline) scheduling pattern. The reference also considers a simultaneous control of sensing and controlling operations, whereas we assume persistent sensing and just focus on the transmission of updates as the degree of freedom of the scheduler.…”

Section: Related Workmentioning

confidence: 99%

Impact of Transmission Delays Over Age of Information Under Finite Horizon Scheduling

Zancanaro,

Cisotto,

Munari

et al. 2023

2023 IEEE 28th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)

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Sensor communications in real-time systems may be required to report status updates to minimize the so-called age of information metric, which quantifies the freshness of exchanged data. This situation can be heavily impacted by the delays in data transmission, as some updates may reach the destination when their information content is already stale. In this paper, we consider the problem of scheduling sensing updates over a finite time horizon, and discuss the impact of their transmission delay on the resulting data freshness. We tackle the adjustments required for an offline schedule aimed at minimizing the average age of information which, as long as they do not cause the updates to go off the boundaries of the finite horizon, are only dependent on the average transmission delay. We derive a closed form expression for the average age of information, also verified through simulations, and the resulting performance is evaluated under different system conditions. This can be used to further explore the task of delivering timely system updates under general scenarios, e.g., when the statistics of the delay is not known a priori, or under other non idealities.

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“…A further work of multi-source for minimizing age was proposed in [15], where the sources are controlled by a scheduler that decides which source should sample. And the two-way delay between sensor and controller was considered in [16]. Nevertheless, the sampling and scheduling problem in multi-dimensional case is still open.…”

Section: Related Workmentioning

confidence: 99%

Optimal sampling policy of multi‐dimensional wiener processes with random delivery time

Peng

Chen

Gong

2021

IET Control Theory & Appl

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A sampling problem for remote monitoring and estimation of the multi-dimensional Wiener process through a channel with random delivery time under the constraint of maximum sampling frequency is considered. The authors study the optimal sampling policy that minimizes the mean square error. It is showed that the threshold policy is optimal and the near closed-form expressions of the optimal threshold and the corresponding mean square error are given. A bisection method is proposed to search the numerical solutions. The results provide a general framework for remote estimation and sampling, including the special cases that the dimension of Wiener source is one and that the delivery time of the channel tends to zero. Simulation results show that even though there is no constraint on the maximum sampling frequency, age-optimal policy, periodic sampling policy and zero-wait policy are far from optimal.

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Unifying AoI Minimization and Remote Estimation—Optimal Sensor/Controller Coordination With Random Two-Way Delay

Cited by 25 publications

References 24 publications

Optimal Scheduling Policy for Minimizing Age of Information with a Relay

Optimal Scheduling Policy for Minimizing Age of Information with a Relay

Impact of Transmission Delays Over Age of Information Under Finite Horizon Scheduling

Optimal sampling policy of multi‐dimensional wiener processes with random delivery time

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