Hybrid data transmission scheme based on source node centrality and community reconstruction in opportunistic social networks

被引:32
|
作者
Deng, Yepeng [1 ]
Gou, Fangfang [1 ]
Wu, Jia [1 ]
机构
[1] Cent South Univ, Sch Comp Sci & Engn, Changsha 410075, Peoples R China
基金
中国国家自然科学基金;
关键词
Opportunistic social networks; Source node distance; Community restructuring; Task-allocation of data; Steiner minimum tree; MANAGEMENT;
D O I
10.1007/s12083-021-01205-3
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the advent of 5G era and the development of personal mobile devices, people's demand for information and bandwidth is growing exponentially. In the traditional social network and its routing algorithm, there are only a few fixed source nodes and transmission mode. The huge amount of data may lead to delay and loss of data transmission and even the collapse of the source node. In order to solve this problem, this paper proposes an effective data transmission scheme in opportunistic social networks, that is, A source node Centrality and community Restructuring based Hybrid Routing (CRHR) algorithm. The algorithm consists of two parts. In the first part, we measure the centrality of the source node by calculating the critical path where the node is located, and iterate to get the optimal source node and its corresponding relay node. In the second part, we will expand the Opportunity Social Network and rebuild the extended community with the Steiner Minimum Tree to minimize the cost of community data transmission. The simulation results show that the algorithm has lower data transmission delay and cost than other algorithms, and can significantly improve the data transmission rate and efficiency.
引用
收藏
页码:3460 / 3472
页数:13
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