移动社会网络中基于多维上下文匹配的数据转发算法

doi:10.11896/j.issn.1002-137X.2019.02.013

计算机科学 ›› 2019, Vol. 46 ›› Issue (2): 81-87.doi: 10.11896/j.issn.1002-137X.2019.02.013

移动社会网络中基于多维上下文匹配的数据转发算法

徐方^1,2, 邓敏¹, 熊曾刚¹, 叶从欢¹, 徐宁²

湖北工程学院计算机与信息科学学院湖北孝感432000¹
武汉大学计算机学院武汉430072²

收稿日期:2018-01-07 出版日期:2019-02-25 发布日期:2019-02-25
通讯作者: 邓敏(1983－),女,硕士,讲师,主要研究方向为计算机网络,E-mail:dm2010@whu.edu.cn
作者简介:徐方(1981－),男,博士,副教授,硕士生导师,CCF会员,主要研究方向为无线移动网络、智能感知计算;熊曾刚(1974－),男,博士,教授,硕士生导师,主要研究方向为计算机网络、云计算;叶从欢(1980-),男,博士,副教授,硕士生导师,主要研究方向为社交多媒体;徐宁(1989－),男,博士生,主要研究方向为无线移动网络、智能感知计算。
基金资助:
本文受教育部人文社会科学研究青年基金项目(17YJCZH203),湖北省教育厅科研计划重点项目(D20182702)资助。

Data Forwarding Algorithm Based on Multidimensional Context Matching in Mobile Social Networks

XU Fang^1,2, DENG Min¹, XIONG Zeng-gang¹, YE Cong-huan¹, XU Ning²

School of Computer and Information Science,Hubei Engineering University,Xiaogan,Hubei 432000,China¹
School of Computer Science,Wuhan University,Wuhan 430072,China²

Received:2018-01-07 Online:2019-02-25 Published:2019-02-25

摘要/Abstract

摘要： 通过研究移动社会网络中的多种上下文信息对节点移动模式的影响,提出了基于多维上下文认知的数据转发算法MCMF。该算法综合考虑物理邻接性、社会相似性以及社会交互性3个维度的上下文信息来进行动态数据转发决策。首先消息携带者节点通过物理邻接匹配获得邻居节点集合;然后通过社会相似性匹配在邻居节点集合中选出候选节点子集,并基于社会网络的社群特征,采用马尔可夫预测方法在候选节点子集中选出最优中继节点;最后设计高效的数据转发算法。仿真实验表明,相比于其他3种著名算法,该算法在交付比率和开销比率方面具有较好的性能。

关键词: 多维, 上下文匹配, 移动社会网络, 预测模型, 转发算法

Abstract: Through studying the effect of a variety of context information on the mobility patterns in mobile social networks,this paper proposed a multidimensional context matching forwarding (MCMF) algorithm.In this novel algorithm,three dimension contexts,which are physical adjacency,social similarity and social interactivity,are used to make routing decisions dynamically.Firstly,message carrier obtains its neighbor node sets by using physical adjacency matching at the present moment.Then social similarity matching is used to search relay candidate subset of neighbor node sets,and the discrete-time semi-Markov prediction model is used to determine the best relay node.At last,the efficient data forwarding algorithm is designed.Simulation experiments based on real traces show that the proposed MCMF algorithm is more efficient in terms of maximizing the delivery ratio and minimizing the overhead ratio than other three state-of-the-art algorithms.

Key words: Context matching, Forwarding algorithm, Mobile social networks, Multi dimensional, Prediction model

中图分类号:

TN915

徐方, 邓敏, 熊曾刚, 叶从欢, 徐宁. 移动社会网络中基于多维上下文匹配的数据转发算法[J]. 计算机科学, 2019, 46(2): 81-87. https://doi.org/10.11896/j.issn.1002-137X.2019.02.013

XU Fang, DENG Min, XIONG Zeng-gang, YE Cong-huan, XU Ning. Data Forwarding Algorithm Based on Multidimensional Context Matching in Mobile Social Networks[J]. Computer Science, 2019, 46(2): 81-87. https://doi.org/10.11896/j.issn.1002-137X.2019.02.013

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移动社会网络中基于多维上下文匹配的数据转发算法

Data Forwarding Algorithm Based on Multidimensional Context Matching in Mobile Social Networks

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