Efficient Data Transmission for Community Detection Algorithm Based on Node Similarity in Opportunistic Social Networks
With the rapid development of 5G era, the number of messages on the network has increased sharply. The traditional opportunistic networks algorithm has some shortcomings in processing data. Most traditional algorithms divide the nodes into communities and then perform data transmission according to...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/9928771 |
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| _version_ | 1832554566053265408 |
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| author | Aizimaiti Xiaokaiti Yurong Qian Jia Wu |
| author_facet | Aizimaiti Xiaokaiti Yurong Qian Jia Wu |
| author_sort | Aizimaiti Xiaokaiti |
| collection | DOAJ |
| description | With the rapid development of 5G era, the number of messages on the network has increased sharply. The traditional opportunistic networks algorithm has some shortcomings in processing data. Most traditional algorithms divide the nodes into communities and then perform data transmission according to the divided communities. However, these algorithms do not consider enough nodes’ characteristics in the communities’ division, and two positively related nodes may divide into different communities. Therefore, how to accurately divide the community is still a challenging issue. We propose an efficient data transmission strategy for community detection (EDCD) algorithm. When dividing communities, we use mobile edge computing to combine network topology attributes with social attributes. When forwarding the message, we select optimal relay node as transmission according to the coefficients of channels. In the simulation experiment, we analyze the efficiency of the algorithm in four different real datasets. The results show that the algorithm has good performance in terms of delivery ratio and routing overhead. |
| format | Article |
| id | doaj-art-580a7d9c66ee4b329401dc79bbdf4332 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-580a7d9c66ee4b329401dc79bbdf43322025-02-03T05:51:12ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/99287719928771Efficient Data Transmission for Community Detection Algorithm Based on Node Similarity in Opportunistic Social NetworksAizimaiti Xiaokaiti0Yurong Qian1Jia Wu2Software College, Xinjiang University, Urumqi 830000, ChinaSoftware College, Xinjiang University, Urumqi 830000, ChinaSchool of Computer Science and Engineering, Central South University, Changsha 410083, ChinaWith the rapid development of 5G era, the number of messages on the network has increased sharply. The traditional opportunistic networks algorithm has some shortcomings in processing data. Most traditional algorithms divide the nodes into communities and then perform data transmission according to the divided communities. However, these algorithms do not consider enough nodes’ characteristics in the communities’ division, and two positively related nodes may divide into different communities. Therefore, how to accurately divide the community is still a challenging issue. We propose an efficient data transmission strategy for community detection (EDCD) algorithm. When dividing communities, we use mobile edge computing to combine network topology attributes with social attributes. When forwarding the message, we select optimal relay node as transmission according to the coefficients of channels. In the simulation experiment, we analyze the efficiency of the algorithm in four different real datasets. The results show that the algorithm has good performance in terms of delivery ratio and routing overhead.http://dx.doi.org/10.1155/2021/9928771 |
| spellingShingle | Aizimaiti Xiaokaiti Yurong Qian Jia Wu Efficient Data Transmission for Community Detection Algorithm Based on Node Similarity in Opportunistic Social Networks Complexity |
| title | Efficient Data Transmission for Community Detection Algorithm Based on Node Similarity in Opportunistic Social Networks |
| title_full | Efficient Data Transmission for Community Detection Algorithm Based on Node Similarity in Opportunistic Social Networks |
| title_fullStr | Efficient Data Transmission for Community Detection Algorithm Based on Node Similarity in Opportunistic Social Networks |
| title_full_unstemmed | Efficient Data Transmission for Community Detection Algorithm Based on Node Similarity in Opportunistic Social Networks |
| title_short | Efficient Data Transmission for Community Detection Algorithm Based on Node Similarity in Opportunistic Social Networks |
| title_sort | efficient data transmission for community detection algorithm based on node similarity in opportunistic social networks |
| url | http://dx.doi.org/10.1155/2021/9928771 |
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