A comprehensive survey on age of information in massive IoT networks

Q Abbas, SA Hassan, HK Qureshi, K Dev… - Computer …, 2023 - Elsevier
Ambient intelligence (AmI) represents the future vision of intelligent computing that can bring
intelligence to our daily life through various domains. In such applications, AmI is often …

Age of information: An introduction and survey

RD Yates, Y Sun, DR Brown, SK Kaul… - IEEE Journal on …, 2021 - ieeexplore.ieee.org
We summarize recent contributions in the broad area of age of information (AoI). In
particular, we describe the current state of the art in the design and optimization of low …

Age of information in energy harvesting aided massive multiple access networks

Z Fang, J Wang, Y Ren, Z Han… - IEEE Journal on …, 2022 - ieeexplore.ieee.org
Given the proliferation of the massive machine type communication devices (MTCDs) in
beyond 5G (B5G) wireless networks, energy harvesting (EH) aided next generation multiple …

Age of information in random access channels

X Chen, K Gatsis, H Hassani… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In applications of remote sensing, estimation, and control, timely communication is critical
but not always ensured by high-rate communication. This work proposes decentralized age …

Optimal sampling and scheduling for timely status updates in multi-source networks

AM Bedewy, Y Sun, S Kompella… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
We consider a joint sampling and scheduling problem for optimizing data freshness in multi-
source systems. Data freshness is measured by a non-decreasing penalty function of age of …

Performance analysis of age of information in ultra-dense Internet of Things (IoT) systems with noisy channels

B Zhou, W Saad - IEEE transactions on wireless …, 2021 - ieeexplore.ieee.org
In this paper, a dense Internet of Things (IoT) monitoring system is studied in which a large
number of devices contend for transmitting timely status packets to their corresponding …

Learning and communications co-design for remote inference systems: Feature length selection and transmission scheduling

MKC Shisher, B Ji, IH Hou, Y Sun - IEEE Journal on Selected …, 2023 - ieeexplore.ieee.org
In this paper, we consider a remote inference system, where a neural network is used to
infer a time-varying target (eg, robot movement), based on features (eg, video clips) that are …

Scheduling with age of information guarantee

C Li, Q Liu, S Li, Y Chen, YT Hou… - IEEE/ACM …, 2022 - ieeexplore.ieee.org
Age of Information (AoI) is an application layer performance metric that quantifies the
freshness of information. This paper investigates scheduling problems at network edge …

Centralized and distributed age of information minimization with nonlinear aging functions in the Internet of Things

T Park, W Saad, B Zhou - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
Resource management in Internet-of-Things (IoT) systems is a major challenge due to the
massive scale and heterogeneity of the IoT system. For instance, most IoT applications …

A Whittle index policy for the remote estimation of multiple continuous Gauss-Markov processes over parallel channels

TZ Ornee, Y Sun - Proceedings of the Twenty-fourth International …, 2023 - dl.acm.org
In this paper, we study a sampling and transmission scheduling problem for multi-source
remote estimation, where a scheduler determines when to take samples from multiple …