Performance evaluation of social relation opportunistic routing in dynamic social networks

Wong, Gary K. W.; Chang, Yanan; Jia, Xiaohua; Wong, Kirk H. M.; Hui, Wing-Yi

doi:10.1109/iccnc.2015.7069461

Cited by 7 publications

(7 citation statements)

References 12 publications

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“…The algorithm is based on social nodes to establish a forwarding model in the opportunistic network and determines whether to forward a message according to a defined stop time [39]. • ICMT: The algorithm evaluates the transfer probability between nodes by identifying surrounding neighbours.…”

Section: Experiments Analysismentioning

confidence: 99%

“…However, the SRBRA algorithm does not con-sider node mobility. Wong et al [39] proposed the social relationship opportunity routing algorithm, which uses the social relationship and configuration files between nodes as key indicators to select relay nodes to optimise routing performance. Souza et al [40] proposed to use the contact frequency of nodes to identify the social relationship of nodes.…”

Section: Related Workmentioning

confidence: 99%

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MNSRQ: Mobile node social relationship quantification algorithm for data transmission in Internet of things

Chen

et al. 2021

IET Communications

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The rapid development of the Internet of things has led to the explosive development of data in various fields. Traditional routing protocols cannot effectively handle the reception and transmission of data. This makes it difficult to exchange and transmit information in the Internet of things. Therefore, the choice of data transmission methods is particularly important. In order to solve this problem, this paper proposes a data transmission mechanism based on social relationships, namely, the mobile node social relationship quantification (MNSRQ) algorithm, which analyses the social relationship characteristics of mobile nodes in the Internet of things, extracts decision-making features to study the dynamics of social relationship, then combines information entropy and fuzzy clustering theory to quantify the social relationship, and then selects the relay node with strong social relationship for data transmission. Theoretical analysis and experimental results show that the performance of the MNSRQ algorithm is better than previous studies. Compared with epidemic algorithm, ICMT algorithm, spray and wait algorithm, and EIMST algorithm, the MNSRQ algorithm can reduce end-to-end transmission delay and routing overhead while maintaining the life of the network, effectively reduce energy consumption during transmission, and maintain a high data transmission success rate, with a transmission success rate of 0.7-0.9. 1 This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Experiments Analysismentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

MNSRQ: Mobile node social relationship quantification algorithm for data transmission in Internet of things

Chen

et al. 2021

IET Communications

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“…In the opportunistic network, it has been proven that the user's social profiles are useful for finding suitable forwarding nodes in a delay tolerant network. A Social Relationship Opportunistic Routing Algorithm (SROR) [14] was proposed for mobile social networks. Social relations and profiles between nodes were used as the key indicators for calculating the optimal forwarding node in the route to maximize the packet transmission probability.…”

Section: Related Workmentioning

confidence: 99%

Quantitative social relations based on trust routing algorithm in opportunistic social network

Chen

et al. 2019

J Wireless Com Network

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The trust model is widely used in the opportunistic social network to solve the problem of malicious nodes and information flooding. The previous method judges whether the node is a cooperative node through the identity authentication, forwarding capability, or common social attribute of the destination node. In real applications, this information does not have integrity and does not take into account the characteristics and dynamic adaptability of nodes, network structures, and the transitivity of social relationships between nodes. Therefore, it may not be effective in solving node non-cooperation problems and improving transmission success rate. To address this problem, the proposed node social features relationship evaluation algorithm (NSFRE) establishes a fuzzy similarity matrix based on various features of nodes. Each node continuously and iteratively deletes the filtered feature attributes to form a multidimensional similarity matrix according to the confidence level and determines the weights under different feature attributes. Then, the social relations of nodes are further quantified. The experimental results show that, compared with the traditional routing algorithm, NSFRE algorithm can effectively improve the transmission success rate, reduce transmission delay, ensure the safe and reliable transmission of information in the network, and require low buffer space and computing capacity.

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“…Hence, no complete path exists between the source and destination nodes. 17 IoT has some features of a delay-tolerant network (DTN) because it originates from the DTN and the MANET. However, when the network is interrupted, the DTN regards it as a network fault, while IoT considers it normal and reconnects them using the node mobility.…”

Section: Related Workmentioning

confidence: 99%

DTSW: A data transmission scheme based on weighted security partition model in industrial Internet of Things environment

Zhu

Zheng

Huang

et al. 2019

Advances in Mechanical Engineering

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With the rapid development of industrial Internet of Things, the secure transmission of nodes in Internet of Things is easily attacked by malicious nodes at all times, thereby causing a great threat to network performance and security of industrial Internet of Things. To improve the security and success rate of data transmission in industrial Internet of Things environment, this work proposes a data transmission scheme based on the weighted security partition model by considering the requirements of a hostile industrial environment. The weighted security partition of the nodes determines the secret distribution model. On this basis, a secure authentication scheme for network transmission is proposed for industrial Internet of Things to prevent the data from being tampered by malicious industrial nodes. Authority access control is added to the authentication scheme. The network access authority of users is used to eliminate the access of malicious users. Finally, the simulation experiments and performance evaluation are conducted and compared with other secure transmission algorithms. Results show that, by comparing to low-energy adaptive clustering hierarchy and distributed data secure transmission, the transmission rate of the proposed algorithm has increased by 35% and 25%, and the lifetime has increased by 34.3% and 37.3%, respectively.

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Performance evaluation of social relation opportunistic routing in dynamic social networks

Cited by 7 publications

References 12 publications

MNSRQ: Mobile node social relationship quantification algorithm for data transmission in Internet of things

MNSRQ: Mobile node social relationship quantification algorithm for data transmission in Internet of things

Quantitative social relations based on trust routing algorithm in opportunistic social network

DTSW: A data transmission scheme based on weighted security partition model in industrial Internet of Things environment

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