A stackelberg differential game based bandwidth allocation in satellite communication network

Su, Jingtao; Yang, Shengsong; Xu, Haitao; Zhou, Xianwei

doi:10.1109/cc.2018.8438284

Cited by 22 publications

(5 citation statements)

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“…For instance, Su et al have developed a differential game model for bandwidth allocation in satellite communication networks by combining differential equations with Stackelberg games. The solutions to these games were determined by solving Bellman's dynamic equations, and the methods' validity was confirmed through simulation experiments [80] . Similarly, Liu et al proposed a model based on Stackelberg differential games for wireless network resource allocation, aimed at optimizing resource distribution in fog computing scenarios.…”

Section: Differential Gamementioning

confidence: 96%

Resource Allocation for Space-Air-Ground Integrated Networks: A Comprehensive Review

Liang,

Yang,

Zhang

et al. 2024

J. Commun. Inf. Netw.

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The space-air-ground integrated networks (SAGIN) has emerged as a critical paradigm to address the growing demands for global connectivity and enhanced communication services. This paper gives a thorough review of the strategies and methodologies for resource allocation within SAGIN, focusing on the challenges and solutions within its complex structure. With the advent of technologies such as 6G, the dynamics of resource optimization have become increasingly complex, necessitating innovative approaches for efficient management. We examine the application of mathematical optimization, game theory, artificial intelligence (AI), and dynamic optimization techniques in SAGIN, offering insights into their effectiveness in ensuring optimal resource distribution, minimizing delays, and maximizing network throughput and stability. The survey highlights the significant advances in AI-based methods, particularly deep learning and reinforcement learning, in tackling the inherent challenges of SAGIN resource allocation. Through a critical review of existing literature, this paper categorizes various resource allocation strategies, identifies current research gaps, and discusses potential future directions. Our findings highlight the crucial role of integrated and intelligent resource allocation mechanisms in realizing the full potential of SAGIN for Manuscript

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Section: Differential Gamementioning

confidence: 96%

Resource Allocation for Space-Air-Ground Integrated Networks: A Comprehensive Review

Liang,

Yang,

Zhang

et al. 2024

J. Commun. Inf. Netw.

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“…As a key bearer for the integration and coordination of operation technology and information and communication technology, fog computing needs to support coordination in connection, data, management, control, application, security, etc. [4][5][6][7][8][9]. The first step is to build the Beidou-1 satellite navigation system (also known as the Beidou satellite navigation test system).…”

Section: The Meaning Of Fog Computingmentioning

confidence: 99%

Development and Application of Big Data in the Field of Satellite Navigation

Zhang

2021

Wireless Communications and Mobile Computing

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Based on the characteristics of big data, the meaning of fog computing, and the spatiotemporal data characteristics of satellite navigation systems, the concept, connotation, and characteristics of Beidou big data were put forward. The Beidou big data processing process was sorted out, the preliminary architecture of the Beidou big data system with fog computing function was built, and finally the fog computing based Beidou big data system was proposed. Big data research content provides technical support for further tapping the value of Beidou satellite navigation system data and realizing the incremental development of satellite navigation systems.

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“…For the context-aware tasks with individual priorities, in order to allocate service resources, we assume that there is a fog computing server in the individual priority groups to control the allocated service resources [19,20]. The fog computing server has enough computing resources to calculate and allocate the appropriate resources for the context-aware tasks based on the task priorities.…”

Section: System Modelmentioning

confidence: 99%

Dynamic Priority-Based Service Resource Allocation for Context-Aware Conflict Resolution in Wisdom Network with Fog Computing

Lin

et al. 2020

Wireless Communications and Mobile Computing

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With the development of wisdom network, this paper assumes that intelligent devices become more and more intelligent, which can easily collect and provide a variety of context awareness data. The research goal is to design a dynamic conflict resolution strategy for context-aware resource allocation. The limited availability of resources inevitably leads to conflicts. Considering the characteristics of wisdom network, the quality of service when solving conflicts, a mechanism is proposed to improve the quality of services and to solve the resources allocation conflicts. This paper constructs the optimal model of context-aware based on a differential game and optimizes the resource allocation of context-aware based on the priority of scenarios. Fog computing is used to provide enough computing resources for the control of resource allocation of context-aware. The Bellman dynamic programming is introduced to solve the feedback Nash equilibrium solution of the proposed differential game model, to obtain the optimal allocation of service resources and solve the effectiveness of resource allocation.

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A stackelberg differential game based bandwidth allocation in satellite communication network

Cited by 22 publications

References 0 publications

Resource Allocation for Space-Air-Ground Integrated Networks: A Comprehensive Review

Resource Allocation for Space-Air-Ground Integrated Networks: A Comprehensive Review

Development and Application of Big Data in the Field of Satellite Navigation

Dynamic Priority-Based Service Resource Allocation for Context-Aware Conflict Resolution in Wisdom Network with Fog Computing

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