Interest Characteristic Probability Predicted Method in Social Opportunistic Networks

Wu, Jia; Yu, Genghua; Guan, Peiyuan

doi:10.1109/access.2019.2915359

Cited by 28 publications

(17 citation statements)

References 24 publications

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“…EITSA [23] divides social communities according to nodes characteristics and it allows information to be transmitted between resource nodes and social communities to achieve good performance with nodes that extend network lifetime and reduce energy consumption in social communication environment. ICPP [24] proposes a method that characteristic interests with neighbors are selected or pushed by users. According to interest characteristic probability predicted method, interest neighbors can be selected and receive or send information.…”

Section: • Replica Based Routingmentioning

confidence: 99%

Design of Routing Protocol for Opportunistic Network Based on Adaptive Motion

et al. 2020

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Opportunistic network takes advantage of the contact opportunities introduced by node movement for data transmission. Data is usually piggybacked during the movement of the carrier, which guarantees its independence, however, the system performance is impaired. Inspired from the motion nature of nodes, this paper proposes an adaptive motion based opportunistic routing protocol to address the problem. It develops a data forwarding priority model from the perspective of data communication and determines data transmission rules in combination with node activity range partition scheme. A differential replica transfer strategy is thus proposed to achieve a tradeoff between transmission efficiency and system overhead. A free motion degree model is constructed based on which a utility function is deduced to choose appropriate nodes for data relaying. The simulation results show that the proposed algorithm achieves higher packet delivery ratio and less transmission latency while satisfying application requirements and restraining network overhead. INDEX TERMS Data forwarding priority, free motion degree, opportunistic routing, utility function, activity range partition.

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Section: • Replica Based Routingmentioning

confidence: 99%

Design of Routing Protocol for Opportunistic Network Based on Adaptive Motion

et al. 2020

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“…Additionally, some community detection schemes were proposed for the applications of mobile social networks. Guan and Wu [53] proposed a novel method that effectively divides social communities according to the human activity characteristics in opportunistic networks [54]. And their established effective information transmission based on structuralization areas scheme allows information to be transmitted between resource nodes and communities [55].…”

Section: B Community Detection Of Mobile Social Networkmentioning

confidence: 99%

Social Community Detection Scheme Based on Social-Aware in Mobile Social Networks

Dian-xing

Wang

2019

IEEE Access

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Currently many factors can influence community detection in mobile social networks, where node mobility is a key factor to influence the stability of community structure. In this paper, we propose a social community detection scheme for mobile social networks based on social-ware, including social attribute similarity, node interest similarity and node mobility. Compared with other community detection schemes, our proposed scheme can accurately detect the communities based on community attribute and node mobility. The experiments show the numbers of detected communities and members in the maximal size community generated by our scheme are both smaller than those of the GN and NM schemes. Additionally, since the nodes (users) both have higher mobility in mobile social networks, the efficiency of our proposed scheme relatively becomes higher. The experiments show when the values of mobility in the test data sets increase, the running time of our proposed scheme decreases when the number of edges is fixed. For example, the running time of our proposed scheme is about 17s when the maximum value of mobility is set as 0.5 and the number of edges is about 16000, and further the running time is only about 13s when the maximum value of mobility is set as 1. Therefore, our proposed scheme can more accurately and efficiently make community detection to increase the stability of mobile community structure. INDEX TERMS Mobile social network, social ware, node mobility, community detection.

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“…ese devices carried by people have the characteristics of random movement and certain human society. It can be regarded as a social node, and the community can be established through the correlation of nodes [12]. In social networks, nodes with a high correlation with others may transmit a large amount of data [13].…”

Section: Introductionmentioning

confidence: 99%

“…For traditional algorithms, many communities deliver information depending on one or two source nodes in the social complex networks. ese nodes not only transmit big volume of data but also require to calculate some tasks, which need more energy consumption [12,[20][21][22][23]. In traditional opportunistic network protocols, if the source node does not have sufficient cache or overhead, it may lead to a long waiting time for data transmission in the community [24].…”

Section: Introductionmentioning

confidence: 99%

Advanced Data Delivery Strategy Based on Multiperceived Community with IoT in Social Complex Networks

Luo

2020

Complexity

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With the advent of 5G communication standards, the number of 5G base stations increases steadily, and the number of mobile terminals and IoT (Internet of Things) devices increases sharply, which sharps a large number of IoT devices and forms a complex network. These devices can take as nodes of a community in the opportunistic social network. However, in the environment of traditional opportunistic network algorithm and mass data transmission, information transmission is only carried out at several source nodes in the community, which usually leads to transmission delay, excessive energy consumption, and source node death. Therefore, we propose an effective data delivery based on the multiperceived domain algorithm, which recombines communities based on the correlation degree of nodes, and new communities assist source nodes to transmit information in solving these problems. The comparison between the experiment and the classical opportunistic network algorithm shows that the method has outstanding performance in reducing the resource consumption of data transmission and improving the efficiency of information transmission.

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Interest Characteristic Probability Predicted Method in Social Opportunistic Networks

Cited by 28 publications

References 24 publications

Design of Routing Protocol for Opportunistic Network Based on Adaptive Motion

Design of Routing Protocol for Opportunistic Network Based on Adaptive Motion

Social Community Detection Scheme Based on Social-Aware in Mobile Social Networks

Advanced Data Delivery Strategy Based on Multiperceived Community with IoT in Social Complex Networks

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