Distributed Multi-node Slicing Model and Application Analysis for Power Information Collection Scene

Chen, Song; Ma, Chao

doi:10.1109/ciced56215.2022.9928895

Cited by 2 publications

(2 citation statements)

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“…This strategy conducts two resource allocations for the slicing layer and the user layer, ensuring fairness while guaranteeing the quality of the user's experience. To address data security concerns in the current information collection scenario, literature [8] introduces a distributed multi-node slicing model based on blockchain. This model is designed to analyze examples and applications for tackling issues like theft, tampering, and destruction during data transmission and storage in the electric power information collection service.…”

Section: Introductionmentioning

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

Preprint

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New services, such as distributed photovoltaic regulation and control, pose new service requirements for 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 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. 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 optimal solutions to the nodes and link mappings of service function chains. The results of our simulation demonstrate that the method proposed in this research enhances resource utilization and meets the QoS requirements of various services.

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Section: Introductionmentioning

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

Preprint

View full text Add to dashboard Cite

show abstract

“…This strategy conducts two resource allocations for the slicing layer and the user layer, ensuring fairness while guaranteeing the quality of the user's experience. To address data security concerns in the current information collection scenario, [12] introduces a distributed multi-node slicing model based on blockchain. This model is designed to analyze examples and applications for tackling issues like theft, tampering, and destruction during data transmission and storage in the electric power information collection service.…”

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.

View full text Add to dashboard Cite

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.

show abstract

Distributed Multi-node Slicing Model and Application Analysis for Power Information Collection Scene

Cited by 2 publications

References 0 publications

A Highly Efficient Resource Slicing and Scheduling Optimization Algorithm for Power Heterogeneous Communication Networks Based on Hypergraph and Congruence Entropy

A Highly Efficient Resource Slicing and Scheduling Optimization Algorithm for Power Heterogeneous Communication Networks Based on Hypergraph and Congruence Entropy

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

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