Efficient Edge Cache Collaboration Transmission Strategy of Opportunistic Social Network in Trusted Community

Wu, Xiaomin; Liu, Chang; Luo, Jingwen; Wu, Jia

doi:10.1109/access.2021.3069992

Cited by 16 publications

(7 citation statements)

References 38 publications

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“…Wu et al [29] proposed the Edge Collaborative Cache Trust Community (ECTC) routing algorithm, which employs comprehensive trust indicators to partition trust communities. This algorithm utilizes explicit labels for direct trust and calculates node similarities through inter-node paths for indirect trust.…”

Section: Related Workmentioning

confidence: 99%

Research on Secure Community Opportunity Network Based on Trust Model

Su,

Liang

2024

Future Internet

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With the innovation of wireless communication technology and the surge of data in mobile networks, traditional routing strategies need to be improved. Given the shortcomings of existing opportunistic routing strategies in transmission performance and security, this paper proposes a community opportunistic routing decision-making method based on the trust model. This algorithm calculates the node’s trust value through the node’s historical forwarding behavior and then calculates the node’s trust value based on the trust model. Thresholds and trust attenuation divide dynamic security communities. For message forwarding, nodes in the security community are prioritized as next-hop relay nodes, thus ensuring that message delivery is always in a safe and reliable environment. On this basis, better relay nodes are further selected for message forwarding based on the node centrality, remaining cache space, and remaining energy, effectively improving the message forwarding efficiency. Through node trust value and community cooperation, safe and efficient data transmission is achieved, thereby improving the transmission performance and security of the network. Through comparison of simulation and opportunistic network routing algorithms, compared with traditional methods, this strategy has the highest transmission success rate of 81% with slightly increased routing overhead, and this algorithm has the lowest average transmission delay.

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Section: Related Workmentioning

confidence: 99%

Research on Secure Community Opportunity Network Based on Trust Model

Su,

Liang

2024

Future Internet

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“…Considering the correlation between cluster set and specific time, a message forwarding routing algorithm based on cluster set named DRAFT was proposed in [29]. In [30], a clustering routing protocol based on the social attributes of nodes is proposed. This protocol defines the dominant and recessive social relationship characteristics of nodes, and assigns the weights of the dominant and recessive features according to the historical data information of the nodes.…”

Section: Iirelated Workmentioning

confidence: 99%

Community Clustering Routing Algorithm Based on Information Entropy in Mobile Opportunity Network

Zhang

Zeng

et al. 2022

IEEE Access

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Aiming at the difficulty of traditional routing clustering algorithms to deal with the different characteristics between communities and the inefficient nodes after community clustering, this paper proposes a Community clustering Routing protocol based on information Entropy in mobile opportunity Networks (CREN). The proposed protocol uses the K-Modes algorithm with unsupervised learning, combined with the pre-selected initial clustering center node to divide the network nodes into the initial clustering community. Then, the communities with similar characteristics are clustered and merged according to the change of information entropy. At the end, a number of different types of communities are formed in the network, and the nodes in the community have a high degree of similarity, which improves the efficiency of message forwarding. At the same time, in order to eliminate the inefficient nodes in the community, based on the information entropy and the social attributes of the nodes, this paper proposes a mechanism for dynamically updating the community to ensure the efficiency of the nodes in the community. The simulation results show that the transmission success rate of this algorithm is better than other classic routing algorithms, meanwhile, it also has lower transmission delay and routing overhead.

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“…However, the large number of copies sprayed on the network will still cause redundancy. Huang et al [25] proposed a Spray and Wait algorithm based on social network location prediction. The algorithm makes full use of node movement information to predict the possible future locations of relay nodes and forwards the copy to a relay closer to the target node.…”

Section: Related Workmentioning

confidence: 99%

A Data Transmission Algorithm Based on Triangle Link Structure Prediction in Opportunistic Social Networks

et al. 2021

Self Cite

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With the popularization of 5G communications, the scale of social networks has grown rapidly, and the types of messages have become increasingly complex. The rapid increases in the number of access nodes and the amount of data have put a greater burden on the transmission of information in the networks. However, when transferring data from a large number of users, the performance of traditional opportunistic network routing algorithms is insufficient, which often leads to problems such as high energy consumption, network congestion, and data packet loss. The way in which to improve this transmission environment has become a difficult task. Therefore, in order to ensure the effective transmission of data and reduce network congestion, this paper proposed a link prediction model based on triangular relationships in opportunistic social networks (LPMBT). In the topological structure of the social network, the algorithm scores links based on the frequency of use and selects the optimal relay node based on the score. It can also efficiently track the target node and reconstruct the sub-community. The simulation experimental results showed that the algorithm had excellent performance, effectively reduced overhead, reduced the end-to-end delay, and greatly improved the data transfer rate in the opportunistic network.

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Efficient Edge Cache Collaboration Transmission Strategy of Opportunistic Social Network in Trusted Community

Cited by 16 publications

References 38 publications

Research on Secure Community Opportunity Network Based on Trust Model

Research on Secure Community Opportunity Network Based on Trust Model

Community Clustering Routing Algorithm Based on Information Entropy in Mobile Opportunity Network

A Data Transmission Algorithm Based on Triangle Link Structure Prediction in Opportunistic Social Networks

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