A Cross-Layer FL-Based Clustering Protocol to Support Multicast Routing in IoT-Enabled MANETs With CF-mMIMO
This paper proposes a novel cross-layer federated learning (FL)-based clustering (CFLC) protocol to support multicast routing in internet of things (IoT)-enabled mobile ad hoc networks (MANETs) with cell-free massive multiple-input multiple-output (CF-mMIMO). The proposed CFLC protocol leverages cro...
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2025-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10824772/ |
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| author | Amalia Amalia Yushintia Pramitarini Ridho Hendra Yoga Perdana Kyusung Shim Beongku An |
| author_facet | Amalia Amalia Yushintia Pramitarini Ridho Hendra Yoga Perdana Kyusung Shim Beongku An |
| author_sort | Amalia Amalia |
| collection | DOAJ |
| description | This paper proposes a novel cross-layer federated learning (FL)-based clustering (CFLC) protocol to support multicast routing in internet of things (IoT)-enabled mobile ad hoc networks (MANETs) with cell-free massive multiple-input multiple-output (CF-mMIMO). The proposed CFLC protocol leverages cross-layer and FL approaches to enhance network stability and connectivity by optimizing cluster head (CH) selection and cluster formation. The cross-layer design integrates physical layer information such as mobility (speed and direction), position, channel capacity, and remaining energy, with network layer information (connectivity) to maximize the cost function value for cluster formation. We design the FL model to improve the clustering performance and satisfy future mobile network requirements. Specifically, during the CH selection step, FL can decide which nodes should be elected as CHs or cluster members (CMs) by using classification. In the cluster formation step, FL addresses a regression problem by optimizing the cost function weights for parameters such as mobility similarity, link quality, remaining energy, and channel capacity to decide which CH each node should follow. The simulation results show that the proposed CFLC protocol outperforms the benchmark protocols in terms of connectivity, scalability, and control overhead. Additionally, the results indicate that the CFLC protocol performs particularly well when using the reference point group mobility (RPGM) model, highlighting its advantage over the random waypoint (RWP) mobility model in maintaining network stability and connectivity. |
| format | Article |
| id | doaj-art-868865591bf649b19647b3adb92a259c |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| series | IEEE Access |
| spelling | doaj-art-868865591bf649b19647b3adb92a259c2025-01-10T00:01:32ZengIEEEIEEE Access2169-35362025-01-01133881389910.1109/ACCESS.2025.352563610824772A Cross-Layer FL-Based Clustering Protocol to Support Multicast Routing in IoT-Enabled MANETs With CF-mMIMOAmalia Amalia0https://orcid.org/0009-0005-9828-5431Yushintia Pramitarini1https://orcid.org/0000-0001-7732-7579Ridho Hendra Yoga Perdana2https://orcid.org/0000-0002-1680-1190Kyusung Shim3https://orcid.org/0000-0003-4851-0811Beongku An4https://orcid.org/0000-0002-0587-3754Department of Software and Communications Engineering, Graduate School, Hongik University, Sejong, Republic of KoreaDepartment of Software and Communications Engineering, Graduate School, Hongik University, Sejong, Republic of KoreaDepartment of Software and Communications Engineering, Graduate School, Hongik University, Sejong, Republic of KoreaSchool of Computer Engineering and Applied Mathematics, Hankyong National University, Anseong, Gyeonggi, Republic of KoreaDepartment of Software and Communications Engineering, Hongik University, Sejong, Republic of KoreaThis paper proposes a novel cross-layer federated learning (FL)-based clustering (CFLC) protocol to support multicast routing in internet of things (IoT)-enabled mobile ad hoc networks (MANETs) with cell-free massive multiple-input multiple-output (CF-mMIMO). The proposed CFLC protocol leverages cross-layer and FL approaches to enhance network stability and connectivity by optimizing cluster head (CH) selection and cluster formation. The cross-layer design integrates physical layer information such as mobility (speed and direction), position, channel capacity, and remaining energy, with network layer information (connectivity) to maximize the cost function value for cluster formation. We design the FL model to improve the clustering performance and satisfy future mobile network requirements. Specifically, during the CH selection step, FL can decide which nodes should be elected as CHs or cluster members (CMs) by using classification. In the cluster formation step, FL addresses a regression problem by optimizing the cost function weights for parameters such as mobility similarity, link quality, remaining energy, and channel capacity to decide which CH each node should follow. The simulation results show that the proposed CFLC protocol outperforms the benchmark protocols in terms of connectivity, scalability, and control overhead. Additionally, the results indicate that the CFLC protocol performs particularly well when using the reference point group mobility (RPGM) model, highlighting its advantage over the random waypoint (RWP) mobility model in maintaining network stability and connectivity.https://ieeexplore.ieee.org/document/10824772/Cell-free massive MIMOclusteringcross-layerfederated learningIoT-enabled mobile ad hoc network |
| spellingShingle | Amalia Amalia Yushintia Pramitarini Ridho Hendra Yoga Perdana Kyusung Shim Beongku An A Cross-Layer FL-Based Clustering Protocol to Support Multicast Routing in IoT-Enabled MANETs With CF-mMIMO IEEE Access Cell-free massive MIMO clustering cross-layer federated learning IoT-enabled mobile ad hoc network |
| title | A Cross-Layer FL-Based Clustering Protocol to Support Multicast Routing in IoT-Enabled MANETs With CF-mMIMO |
| title_full | A Cross-Layer FL-Based Clustering Protocol to Support Multicast Routing in IoT-Enabled MANETs With CF-mMIMO |
| title_fullStr | A Cross-Layer FL-Based Clustering Protocol to Support Multicast Routing in IoT-Enabled MANETs With CF-mMIMO |
| title_full_unstemmed | A Cross-Layer FL-Based Clustering Protocol to Support Multicast Routing in IoT-Enabled MANETs With CF-mMIMO |
| title_short | A Cross-Layer FL-Based Clustering Protocol to Support Multicast Routing in IoT-Enabled MANETs With CF-mMIMO |
| title_sort | cross layer fl based clustering protocol to support multicast routing in iot enabled manets with cf mmimo |
| topic | Cell-free massive MIMO clustering cross-layer federated learning IoT-enabled mobile ad hoc network |
| url | https://ieeexplore.ieee.org/document/10824772/ |
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