Scalable Network Coding for Heterogeneous Devices over Embedded Fields
In complex network environments, there always exist heterogeneous devices with different computational powers. In this work, we propose a novel scalable random linear network coding (RLNC) framework based on embedded fields, so as to endow heterogeneous receivers with different decoding capabilities...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/24/11/1510 |
| _version_ | 1827646658794487808 |
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| author | Hanqi Tang Ruobin Zheng Zongpeng Li Keping Long Qifu Sun |
| author_facet | Hanqi Tang Ruobin Zheng Zongpeng Li Keping Long Qifu Sun |
| author_sort | Hanqi Tang |
| collection | DOAJ |
| description | In complex network environments, there always exist heterogeneous devices with different computational powers. In this work, we propose a novel scalable random linear network coding (RLNC) framework based on embedded fields, so as to endow heterogeneous receivers with different decoding capabilities. In this framework, the source linearly combines the original packets over embedded fields based on a precoding matrix and then encodes the precoded packets over GF(2) before transmission to the network. After justifying the arithmetic compatibility over different finite fields in the encoding process, we derive a sufficient and necessary condition for decodability over different fields. Moreover, we theoretically study the construction of an optimal precoding matrix in terms of decodability. The numerical analysis in classical wireless broadcast networks illustrates that the proposed scalable RLNC not only guarantees a better decoding compatibility over different fields compared with classical RLNC over a single field, but also outperforms Fulcrum RLNC in terms of a better decoding performance over GF(2). Moreover, we take the sparsity of the received binary coding vector into consideration, and demonstrate that for a large enough batch size, this sparsity does not affect the completion delay performance much in a wireless broadcast network. |
| first_indexed | 2024-03-09T19:06:33Z |
| format | Article |
| id | doaj.art-8c9e4fa24283497ba47f1c2d0aae591d |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-09T19:06:33Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-8c9e4fa24283497ba47f1c2d0aae591d2023-11-24T04:35:24ZengMDPI AGEntropy1099-43002022-10-012411151010.3390/e24111510Scalable Network Coding for Heterogeneous Devices over Embedded FieldsHanqi Tang0Ruobin Zheng1Zongpeng Li2Keping Long3Qifu Sun4Department of Communication Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaNetwork Technology Lab, Huawei Technologies Co., Ltd., Shenzhen 518000, ChinaInstitute for Network Sciences and Cyberspace, Tsinghua University, Beijing 100084, ChinaDepartment of Communication Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaDepartment of Communication Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaIn complex network environments, there always exist heterogeneous devices with different computational powers. In this work, we propose a novel scalable random linear network coding (RLNC) framework based on embedded fields, so as to endow heterogeneous receivers with different decoding capabilities. In this framework, the source linearly combines the original packets over embedded fields based on a precoding matrix and then encodes the precoded packets over GF(2) before transmission to the network. After justifying the arithmetic compatibility over different finite fields in the encoding process, we derive a sufficient and necessary condition for decodability over different fields. Moreover, we theoretically study the construction of an optimal precoding matrix in terms of decodability. The numerical analysis in classical wireless broadcast networks illustrates that the proposed scalable RLNC not only guarantees a better decoding compatibility over different fields compared with classical RLNC over a single field, but also outperforms Fulcrum RLNC in terms of a better decoding performance over GF(2). Moreover, we take the sparsity of the received binary coding vector into consideration, and demonstrate that for a large enough batch size, this sparsity does not affect the completion delay performance much in a wireless broadcast network.https://www.mdpi.com/1099-4300/24/11/1510random linear network coding (RLNC)wireless broadcast networkscalable network coding |
| spellingShingle | Hanqi Tang Ruobin Zheng Zongpeng Li Keping Long Qifu Sun Scalable Network Coding for Heterogeneous Devices over Embedded Fields Entropy random linear network coding (RLNC) wireless broadcast network scalable network coding |
| title | Scalable Network Coding for Heterogeneous Devices over Embedded Fields |
| title_full | Scalable Network Coding for Heterogeneous Devices over Embedded Fields |
| title_fullStr | Scalable Network Coding for Heterogeneous Devices over Embedded Fields |
| title_full_unstemmed | Scalable Network Coding for Heterogeneous Devices over Embedded Fields |
| title_short | Scalable Network Coding for Heterogeneous Devices over Embedded Fields |
| title_sort | scalable network coding for heterogeneous devices over embedded fields |
| topic | random linear network coding (RLNC) wireless broadcast network scalable network coding |
| url | https://www.mdpi.com/1099-4300/24/11/1510 |
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