Backpressure-based Mean-field Type Game for Scheduling in Multi-Hop Wireless Sensor Networks
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866917222255951872 |
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| author | Choutri, Salah Eddine Djehiche, Boualem Chauhan, Prajwal Jabari, Saif Eddin |
| author_facet | Choutri, Salah Eddine Djehiche, Boualem Chauhan, Prajwal Jabari, Saif Eddin |
| contents | We propose a Mean-Field Type Game (MFTG) framework for effective scheduling in multi-hop wireless sensor networks (WSNs) using backpressure as a performance criterion. Traditional backpressure algorithms leverage queue differentials to regulate data flow and maintain network stability. In this work, we extend the backpressure framework by incorporating a mean-field term into the cost functional, capturing the global behavior of the system alongside local dynamics. The resulting model utilizes the strengths of non-cooperative mean-field type games, enabling nodes to make decentralized decisions based on both individual queue states and system mean-field effects while accounting for stochastic network interactions. By leveraging the interplay between backpressure dynamics and mean-field coupling, the approach balances local optimization with global efficiency. Numerical simulations demonstrate the efficacy of the proposed method in handling congestion and scheduling in large-scale WSNs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_03059 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Backpressure-based Mean-field Type Game for Scheduling in Multi-Hop Wireless Sensor Networks Choutri, Salah Eddine Djehiche, Boualem Chauhan, Prajwal Jabari, Saif Eddin Systems and Control Optimization and Control We propose a Mean-Field Type Game (MFTG) framework for effective scheduling in multi-hop wireless sensor networks (WSNs) using backpressure as a performance criterion. Traditional backpressure algorithms leverage queue differentials to regulate data flow and maintain network stability. In this work, we extend the backpressure framework by incorporating a mean-field term into the cost functional, capturing the global behavior of the system alongside local dynamics. The resulting model utilizes the strengths of non-cooperative mean-field type games, enabling nodes to make decentralized decisions based on both individual queue states and system mean-field effects while accounting for stochastic network interactions. By leveraging the interplay between backpressure dynamics and mean-field coupling, the approach balances local optimization with global efficiency. Numerical simulations demonstrate the efficacy of the proposed method in handling congestion and scheduling in large-scale WSNs. |
| title | Backpressure-based Mean-field Type Game for Scheduling in Multi-Hop Wireless Sensor Networks |
| topic | Systems and Control Optimization and Control |
| url | https://arxiv.org/abs/2506.03059 |