Hypergraph-Based Resource Allocation for Ultra-Dense Wireless Network in Industrial IoT

Zhuansun, Chenlu; Yan, Kedong; Zhang, Gongxuan; Xiong, Zehui; Huang, Chanying

doi:10.1109/lcomm.2022.3188209

Cited by 5 publications

(3 citation statements)

References 13 publications

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“…Taking Eqs. ( 8), (9), and ( 14) back into delay constraint Formula (7), we can get the maximum value of . According to the given numbers of BSs and front-end cameras, the maximum video uploading ratio that meets real-time transmission can be obtained.…”

Section: Transmission From the Edge To The Cloudmentioning

confidence: 99%

“…Taking industrial manufacturing as an example, sensors are extensively deployed throughout the production process, enabling the realization of intelligent industrial operations through data analysis. This integration of data and intelligence constitutes the foundation of the Industrial Internet of Things (I-IoT) [9] . Among these sensors, the visual sensor holds significant importance in industrial automation, particularly in defect detection.…”

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confidence: 99%

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Feature-Centric Video Transmission and Analytics in Large-Scale Internet of Video Things

Wei,

Liu,

et al. 2024

CAAI Artificial Intelligence Research

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The interconnection of large-scale visual sensors is called the Internet of Video Things (IoVT), which brings a qualitative leap to the interaction of urban information. However, communication delay and resource allocation have brought challenges to the development of IoVT. In this paper, we propose a novel city surveillance IoVT architecture to improve performance. This paradigm consists of front-end target region capture, edge computing and cloud-end feature matching, which can adapt the channel and computing resource allocation ratio flexibly, avoiding communication link congestion caused by unnecessary video uploading. Simulation results show that the proposed scheme is feasible, and can realize efficient data transmission and analysis in an IoVTbased smart city.

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Section: Transmission From the Edge To The Cloudmentioning

confidence: 99%

mentioning

confidence: 99%

Feature-Centric Video Transmission and Analytics in Large-Scale Internet of Video Things

Wei,

Liu,

et al. 2024

CAAI Artificial Intelligence Research

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“…Literature [4] introduces hypergraph theory to deal with sliced links and connections and proposes a new hypergraph-based network slicing framework exploiting the generalization property of hypergraphs to provide faster processing speed and better resource allocation. [5] Transforms the problem of interference reduction in NOMA into a maximum weighted clique set problem in hypergraph theory, obtaining higher spectral efficiency and system performance. In [6], the authors utilizes the hypergraph model to effectively solve the resource allocation problem in heterogeneous ultra-dense networks and significantly improves the spectral efficiency of cellular networks.…”

mentioning

confidence: 99%

A highly efficient resource slicing and scheduling optimization algorithm for power heterogeneous communication networks based on hypergraph and congruence entropy

Wang,

Jiang,

Yang

et al. 2024

EURASIP J. Adv. Signal Process.

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New services, such as distributed photovoltaic regulation and control, pose new service requirements for communication networks in the new power system. These requirements include low latency, high reliability, and large bandwidth. Consequently, power heterogeneous communication networks face the challenge of maintaining quality of service (QoS) while enhancing network resource utilization. Therefore, this paper puts forward a highly efficient optimization algorithm for resource slicing and scheduling in power heterogeneous communication networks. Our first step involves establishing an architectural description model of heterogeneous wireless networks for electric power based on hypergraph. This model characterizes complex dynamic relationships among service requirements, virtual networks, and physical networks. The system congruence entropy characterizes the degree of matching between the service demand and resource supply. Then an optimization problem is formed to maximize the system congruence entropy through dynamic resource allocation. To solve this problem, a joint resource allocation and routing method based on Lagrangian dual decomposition is proposed. These methods provide the optimal solutions of the nodes and link mappings of service function chains. The simulation results demonstrate that the proposed algorithm in this paper can greatly enhance resource utilization and also meet the QoS requirements of various services.

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Swarm Optimization Framework for Energy-Efficient Allocation of Industrial IoT Resources

Saraswat,

Mahajan,

Patil

2023

2023 International Conference on Advances in Computation, Communication and Information Technology (ICAICCIT)

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Hypergraph-Based Resource Allocation for Ultra-Dense Wireless Network in Industrial IoT

Cited by 5 publications

References 13 publications

Feature-Centric Video Transmission and Analytics in Large-Scale Internet of Video Things

Feature-Centric Video Transmission and Analytics in Large-Scale Internet of Video Things

A highly efficient resource slicing and scheduling optimization algorithm for power heterogeneous communication networks based on hypergraph and congruence entropy

Swarm Optimization Framework for Energy-Efficient Allocation of Industrial IoT Resources

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