A Transmission Prediction Mechanism Exploiting Comprehensive Node Forwarding Capability in Opportunistic Networks
Opportunistic network enables users to form an instant network for data sharing, which is a type of Ad-hoc network in nature, thus depends on cooperation between nodes to complete message transmission. Because of intermittent communication and frequent changes of topology structure in opportunistic...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8735738/ |
| _version_ | 1819179486176870400 |
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| author | Peng Zheng Hongxiao Fei Jia Wu Yeqing Yan |
| author_facet | Peng Zheng Hongxiao Fei Jia Wu Yeqing Yan |
| author_sort | Peng Zheng |
| collection | DOAJ |
| description | Opportunistic network enables users to form an instant network for data sharing, which is a type of Ad-hoc network in nature, thus depends on cooperation between nodes to complete message transmission. Because of intermittent communication and frequent changes of topology structure in opportunistic networks, the duration of node encounters is limited, as well as the length of established connections. If the amount of interactive data is large and the communication bandwidth is small, the messages that need to be transmitted are not guaranteed to be delivered successfully every time. In this regard, this paper establishes a transmission prediction mechanism exploiting comprehensive node forwarding capability (TPMEC) in opportunistic networks. When quantifying the forwarding capability of nodes, the algorithm not only considers the cooperative tendency but also discusses the encounter strength between nodes. At the same time, in order to find out all key nodes during the transmission process, the algorithm adopts the theory of matrix decomposition to predict and supplement the missing forwarding capability value of nodes, thus improving the efficiency of message transmission. Simulation results show that compared with ITPCM algorithm, ETNS algorithm, Spray and Wait algorithm, and PRoPHET algorithm, the proposed scheme has the highest transmission success ratio and the lowest routing overhead. |
| first_indexed | 2024-12-22T21:59:12Z |
| format | Article |
| id | doaj.art-c0b802e72b2a456a8105c0f39918008d |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T21:59:12Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-c0b802e72b2a456a8105c0f39918008d2022-12-21T18:11:10ZengIEEEIEEE Access2169-35362019-01-017772387725310.1109/ACCESS.2019.29223508735738A Transmission Prediction Mechanism Exploiting Comprehensive Node Forwarding Capability in Opportunistic NetworksPeng Zheng0https://orcid.org/0000-0001-6169-9239Hongxiao Fei1Jia Wu2https://orcid.org/0000-0001-9013-0818Yeqing Yan3https://orcid.org/0000-0003-4045-7251School of Computer Science and Engineering, Central South University, Changsha, ChinaSchool of Computer Science and Engineering, Central South University, Changsha, ChinaSchool of Computer Science and Engineering, Central South University, Changsha, ChinaSchool of Computer Science and Engineering, Central South University, Changsha, ChinaOpportunistic network enables users to form an instant network for data sharing, which is a type of Ad-hoc network in nature, thus depends on cooperation between nodes to complete message transmission. Because of intermittent communication and frequent changes of topology structure in opportunistic networks, the duration of node encounters is limited, as well as the length of established connections. If the amount of interactive data is large and the communication bandwidth is small, the messages that need to be transmitted are not guaranteed to be delivered successfully every time. In this regard, this paper establishes a transmission prediction mechanism exploiting comprehensive node forwarding capability (TPMEC) in opportunistic networks. When quantifying the forwarding capability of nodes, the algorithm not only considers the cooperative tendency but also discusses the encounter strength between nodes. At the same time, in order to find out all key nodes during the transmission process, the algorithm adopts the theory of matrix decomposition to predict and supplement the missing forwarding capability value of nodes, thus improving the efficiency of message transmission. Simulation results show that compared with ITPCM algorithm, ETNS algorithm, Spray and Wait algorithm, and PRoPHET algorithm, the proposed scheme has the highest transmission success ratio and the lowest routing overhead.https://ieeexplore.ieee.org/document/8735738/Opportunistic networksforwarding capabilitycooperative tendencyencounter strengthmatrix decomposition |
| spellingShingle | Peng Zheng Hongxiao Fei Jia Wu Yeqing Yan A Transmission Prediction Mechanism Exploiting Comprehensive Node Forwarding Capability in Opportunistic Networks IEEE Access Opportunistic networks forwarding capability cooperative tendency encounter strength matrix decomposition |
| title | A Transmission Prediction Mechanism Exploiting Comprehensive Node Forwarding Capability in Opportunistic Networks |
| title_full | A Transmission Prediction Mechanism Exploiting Comprehensive Node Forwarding Capability in Opportunistic Networks |
| title_fullStr | A Transmission Prediction Mechanism Exploiting Comprehensive Node Forwarding Capability in Opportunistic Networks |
| title_full_unstemmed | A Transmission Prediction Mechanism Exploiting Comprehensive Node Forwarding Capability in Opportunistic Networks |
| title_short | A Transmission Prediction Mechanism Exploiting Comprehensive Node Forwarding Capability in Opportunistic Networks |
| title_sort | transmission prediction mechanism exploiting comprehensive node forwarding capability in opportunistic networks |
| topic | Opportunistic networks forwarding capability cooperative tendency encounter strength matrix decomposition |
| url | https://ieeexplore.ieee.org/document/8735738/ |
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