Age-Driven Spatially Temporally Correlative Updating in the Satellite-Integrated Internet of Things via Markov Decision Process

Li, Yue; Xu, Yunlai; Zhang, Qinyu; Yang, Zhihua

doi:10.1109/jiot.2022.3142268

Cited by 5 publications

(3 citation statements)

References 32 publications

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“…The research in [ 114 ] focuses on the problem of maintaining fast data updates in satellite-integrated IoT networks for applications like animal tracking and environmental monitoring. To address this, the authors propose Spatially Temporally Correlative Mutual Information (STI), a new metric that takes into account correlations between the most recent update message and the current state of the data source.…”

Section: Iort Systems Based On Space-borne Ntn Networkmentioning

confidence: 99%

Non-Terrestrial Networks for Energy-Efficient Connectivity of Remote IoT Devices in the 6G Era: A Survey

Plastras,

Tsoumatidis,

Skoutas

et al. 2024

Sensors

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The Internet of Things (IoT) is gaining popularity and market share, driven by its ability to connect devices and systems that were previously siloed, enabling new applications and services in a cost-efficient manner. Thus, the IoT fuels societal transformation and enables groundbreaking innovations like autonomous transport, robotic assistance, and remote healthcare solutions. However, when considering the Internet of Remote Things (IoRT), which refers to the expansion of IoT in remote and geographically isolated areas where neither terrestrial nor cellular networks are available, internet connectivity becomes a challenging issue. Non-Terrestrial Networks (NTNs) are increasingly gaining popularity as a solution to provide connectivity in remote areas due to the growing integration of satellites and Unmanned Aerial Vehicles (UAVs) with cellular networks. In this survey, we provide the technological framework for NTNs and Remote IoT, followed by a classification of the most recent scientific research on NTN-based IoRT systems. Therefore, we provide a comprehensive overview of the current state of research in IoRT and identify emerging research areas with high potential. In conclusion, we present and discuss 3GPP’s roadmap for NTN standardization, which aims to establish an energy-efficient IoRT environment in the 6G era.

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Section: Iort Systems Based On Space-borne Ntn Networkmentioning

confidence: 99%

Non-Terrestrial Networks for Energy-Efficient Connectivity of Remote IoT Devices in the 6G Era: A Survey

Plastras,

Tsoumatidis,

Skoutas

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

“…Most of the existing literature focuses on the effective information at individual node locations. Therefore, as an comparison approach abbreviated as STI-based scheduling, we referred to reference [ 30 ], which uses point spatially and temporally correlative mutual information at the sensor location as a metric for system scheduling. In other words, in the modeling scenario of this paper, the STI-based scheduling activates the node with the least point of spatially and temporally information based on the point of spatially temporally information of each node location at each moment.…”

Section: Experimental Evaluationmentioning

confidence: 99%

“…In [ 28 , 29 ], an optimal scheduling policy over limited communication channels is derived that minimizes the time-average mean squared error (MSE). A novel timeliness metric with spatially and temporally correlative mutual information (STI) is proposed in [ 30 ], where an optimal update interval is found by solving an integer optimization problem. Assuming that the information can be commonly observed by multiple sensors, two multi-source information update problems are formulated in [ 31 ].…”

Section: Introductionmentioning

confidence: 99%

Efficient Sensor Scheduling Strategy Based on Spatio-Temporal Scope Information Model

Liu

Chen

Qin

et al. 2023

Sensors

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In this paper, based on the information entropy and spatio-temporal correlation of sensing nodes in the Internet of Things (IoT), a Spatio-temporal Scope Information Model (SSIM) is proposed to quantify the scope of the valuable information of sensor data. Specifically, the valuable information of sensor data decays with space and time, which can be used to guide the system to make efficient sensor activation scheduling decisions for regional sensing accuracy. A simple sensing and monitoring system with three sensor nodes is investigated in this paper, and a single-step scheduling decision mechanism is proposed for the optimization problem of maximizing valuable information acquisition and efficient sensor activation scheduling in the sensed region. Regarding the above mechanism, the scheduling results and approximate numerical bounds on the node layout between different scheduling results are obtained through theoretical analyses, which are consistent with simulation. In addition, a long-term decision mechanism is also proposed for the aforementioned optimization issues, where the scheduling results with different node layouts are derived by modeling as a Markov decision process and utilizing the Q-learning algorithm. Concerning the above two mechanisms, the performance of both is verified by conducting experiments using the relative humidity dataset; furthermore, the differences in performance and limitations of the model are discussed and summarized.

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Improving Information Freshness via Backbone-Assisted Cooperative Access Points

Pan

Zhou

Chan

et al. 2023

IEEE Internet Things J.

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Age-Driven Spatially Temporally Correlative Updating in the Satellite-Integrated Internet of Things via Markov Decision Process

Cited by 5 publications

References 32 publications

Non-Terrestrial Networks for Energy-Efficient Connectivity of Remote IoT Devices in the 6G Era: A Survey

Non-Terrestrial Networks for Energy-Efficient Connectivity of Remote IoT Devices in the 6G Era: A Survey

Efficient Sensor Scheduling Strategy Based on Spatio-Temporal Scope Information Model

Improving Information Freshness via Backbone-Assisted Cooperative Access Points

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