[1]许岗,金海和,刘靖.非稳态拓扑下的机会网络分层模型[J].东南大学学报(自然科学版),2015,45(3):438-442.[doi:10.3969/j.issn.1001-0505.2015.03.005]
 Xu Gang,Jin Haihe,Liu Jing.Opportunistic network hierarchical model in unsteady topology[J].Journal of Southeast University (Natural Science Edition),2015,45(3):438-442.[doi:10.3969/j.issn.1001-0505.2015.03.005]
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非稳态拓扑下的机会网络分层模型()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
45
期数:
2015年第3期
页码:
438-442
栏目:
计算机科学与工程
出版日期:
2015-05-20

文章信息/Info

Title:
Opportunistic network hierarchical model in unsteady topology
作者:
许岗1金海和12刘靖1
1内蒙古大学计算机学院, 呼和浩特 010021; 2内蒙古大学公共管理学院, 呼和浩特 010021
Author(s):
Xu Gang1 Jin Haihe12 Liu Jing1
1College of Computer Science, Inner Mongolia University, Huhhot 010021, China
2College of Public Management, Inner Mongolia University, Huhhot 010021, China
关键词:
机会网络 敏感性 虚拟机会网络分层模型 社团划分
Keywords:
opportunistic network sensitivity virtual opportunistic network hierarchical model community detection
分类号:
TP393
DOI:
10.3969/j.issn.1001-0505.2015.03.005
摘要:
为了解决在消息敏感的机会网络中社团划分结果不可重用的问题,提出了一种与消息类型相匹配的机会网络分层模型.首先,将机会网络的物理节点集映射为与消息类型匹配的虚拟节点集,并以此为基础建立虚拟机会网络层;然后,在虚拟机会网络层上,建立虚拟节点集的社会关系;最后,对虚拟节点集的社会关系进行社团划分.实验结果表明:在消息数量相同的条件下,当消息序列中相邻位置消息的类型差异度分别为40%和100%时,在虚拟层上进行社团划分的时间与在物理机会网络上直接进行社团划分的时间相比分别减少约58%和89%;基于分层模型的社团划分的运行次数仅依赖于消息类型的数量,而不会随消息数量或消息序列中不同类型消息交错方式的变化而变化.
Abstract:
In order to solve the problem that the community detection results cannot be repeatedly used in the information sensitivity opportunistic network, an opportunistic network hierarchical model which matches with information types is proposed. First, the physical node set in the opportunistic network is mapped as a virtual node set which matches with information types, based on which the virtual opportunistic network layer is established. Then, the social relationship of the virtual node set is built on the virtual opportunistic network layer. Finally, community detection is conducted on the social relationship of the virtual node set. The experimental results show that when the difference degrees of the types of adjacent information in the information sequence are 40% and 100%, the time consumption in community detection on the virtual layer decreases by about 58% and 89% compared with that in the physical opportunistic network with the same information quantity, respectively. The execution number of the community detection operations based on the layer model only depends on the number of the information types, and does not change with the change of the information quantity or the overlapping ways of the different information types in the information sequence.

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备注/Memo

备注/Memo:
收稿日期: 2014-10-31.
作者简介: 许岗(1980—),男,博士生,讲师;金海和(联系人),男,博士,教授,博士生导师, jin_haihe@126.com.
基金项目: 内蒙古自治区自然科学基金资助项目(2013MS0904).
引用本文: 许岗,金海和,刘靖.非稳态拓扑下的机会网络分层模型[J].东南大学学报:自然科学版,2015,45(3):438-442. [doi:10.3969/j.issn.1001-0505.2015.03.005]
更新日期/Last Update: 2015-05-20