Efficient Data Transmission for Community Detection Algorithm Based on Node Similarity in Opportunistic Social Networks

Xiaokaiti, Aizimaiti; Qian, Yurong; Wu, Jia

doi:10.1155/2021/9928771

Cited by 13 publications

(5 citation statements)

References 44 publications

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Section: Related Workmentioning

confidence: 99%

“…Wu et al [21][22][23] use the node social relationship in the network to transmit data efficiently. Firstly, they proposed the mobile node social relationship quantification (MNSRQ) algorithm [21], which through calculating the social relationship of mobile nodes to select the appropriate relay node to transmit data.…”

Section: Related Workmentioning

confidence: 99%

“…This method also use the user's social relationship, meanwhile, the release location of the interest is also taken into account. In literature [23], they combined mobile edge computing of network topology attributes with social attributes for community detection. Magaia et al [24] also use the social relationship characteristics of nodes to cluster through machine learning method, and they proposed an efficient routing scheme for internet of vehicles (IoV).…”

Section: Related Workmentioning

confidence: 99%

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Clustered DTN routing based on sensing node relationship strength

Chen,

2024

IET Communications

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Delay tolerant networks (DTNs) is a network evolved from mobile networks. Differing from the traditional network, which has a stable end‐to‐end transmission path, DTNs are sparse and intermittently connected mobile ad hoc network, which are widely used in harsh environments, such as battlefields, seabed, space communication networks, and so on. In DTNs, intermittent connectivity, partitioned network, long delays and node mobility characteristics make the network fail to communicate frequently, therefore, how to successfully forward the message is of extreme importance. Up to now, almost all the traditional models in DTNs use the store‐carry‐forward method. This paper proposes a novel clustered DTN routing model based on sensing node relationship strength. The routing mechanism takes advantage of the number of other nodes encountered by the nodes in the process of movement and the changes in the number of nodes to calculate the strength of the relationship between nodes, and clusters DTN routing according to the strength of the relationship between nodes. Moreover, the relationship between nodes in a cluster and other clusters is used to transmit messages between clusters, and messages are transmitted within clusters according to the strength of the relationship between nodes. Simulation results show that the routing mechanism not only increases the success rate of message transmission, but also reduces the transmission delay of messages and improves network performance.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Clustered DTN routing based on sensing node relationship strength

Chen,

2024

IET Communications

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“…The PriNergy technology increases the robustness of the routing protocol. Aizimaiti Xiaokaiti et al [29] proposed a community detection and data transmission strategy, called EDCD, which considers node characteristics. This method selects the optimal relay node for transmission based on channel coefficients.…”

Section: Related Workmentioning

confidence: 99%

An effective data communication community establishment scheme in opportunistic networks

Hao

Gou

2023

IET Communications

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The network transmission speed has been greatly improved, thanks to the power of 5G technology. The millisecond‐level communication delay has made a qualitative leap in communication quality. However, the sharp increase in the number of nodes connected to the internet has resulted in an explosion of traffic. Ensuring stable network transmission in the face of large data volumes has become an urgent problem to be solved. Existing research mainly optimizes for low data volumes of nodes, and cannot dynamically adapt to node transmission load to cope with explosive growth. This is because the node's cache is always at a high level, which causes community communication to be blocked. To address this issue, the authors have designed an effective data communication community establishment scheme. By adding a data information flow (DIF) attribute to each user and using the dynamic feedback adjustment (DFA) mechanism, the authors can combine the entire communication community and control the user's data information flow concentration at a relatively low level. This degree of optimization ensures that the user node maintains a relatively stable state for fast communication. The authors design an effective data communication community establishment scheme. By adding a data information flow (DIF) attribute to each user, using the dynamic feedback adjustment mechanism and combining the entire communication community, the user's data information flow concentration is controlled at a relatively low level.

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“…In the category of social network modeling, the article by Xiaokaiti et al [13], "Efficient Data Transmission for Community Detection Algorithm Based on Node Similarity in Opportunistic Social Networks," studied the problem of community detection and presented a new data transmission method which considers social attributes. In the article titled "Layer Information Similarity Concerned Network Embedding," by Lu et al [14], the authors explored the method of network embedding and they introduced the layer information similarity to enhance the representation of nodes.…”

mentioning

confidence: 99%