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DOI:
Journal of Software:2018.29(S1):92-104

一种基于节点行为模式的相似性指标
舒坚,马玉良,林伟杰,刘琳岚
(南昌航空大学 物联网技术研究所, 江西 南昌 330063;南昌航空大学 软件学院, 江西 南昌 330063;南昌航空大学 物联网技术研究所, 江西 南昌 330063;南昌航空大学 信息工程学院, 江西 南昌 330063)
Similarity Index Based on Node Behavior Patterns
SHU Jian,MA Yu-Liang,LIN Wei-Jie,LIU Lin-Lan
(Internet of Things Technology Institute, Nanchang HangKong University, Nanchang 330063, China;School of Software, Nanchang HangKong University, Nanchang 330063, China;Internet of Things Technology Institute, Nanchang HangKong University, Nanchang 330063, China;School of Information Engineering, Nanchang HangKong University, Nanchang 330063, China)
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Received:May 01, 2018    
> 中文摘要: 手持设备网络(PSN)是一种利用节点移动和机会性相遇进行数据交互的延迟容忍网络(DTN).由于PSN具有网络拓扑不断变化、节点间链接时变性等特点,导致常用的节点间相似性评价方法不能很好地被应用于PSN的链路预测.针对PSN网络节点的行为特点,分析节点间产生连接次数、连接持续时间以及节点访问区域的规律,将PSN网络中节点的相似性分为节点社交行为相似性和移动行为相似性.结合社交行为相似性以及节点移动行为相似性,比较其在不同加权系数下的AUC和Precision,提出基于节点行为模式的相似性指标(SNBP).在MIT Reality以及Dartmouth Campus数据集上的结果表明:与CN、AA和Katz相似性指标相比,所提出的相似性指标具有更好的预测准确率.
Abstract:Pocket switched networks (PSN) is a kind of delay tolerant network (DTN) which transmits messages based on node movement and opportunity encounter. The traditional similarity index based prediction methods are not suitable for the link prediction of PSN due to the frequent topology change and time-various link in PSN. According to the characteristics of PSN node behavior, this paper analyzes connection time, connection duration, and the law of node accessing areas. Node similarity is categorized into sociality behavior similarity and movement behavior similarity. After comparing AUC and Precision with different weight for sociality behavior similarity and movement behavior similarity, similarity index based on node behavior patterns (SNBP) is proposed. The experiment results on MIT Reality and Dartmouth Campus datasets show that comparison with CN, AA, and Katz similarity index, the proposed similarity index has better precision.
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基金项目:国家自然科学基金(61762065,61363015,61262020);江西省自然科学基金(20171ACB20018,20171BAB202009,20171BBH80022);江西省研究生创新专项资金(YC2018093) 国家自然科学基金(61762065,61363015,61262020);江西省自然科学基金(20171ACB20018,20171BAB202009,20171BBH80022);江西省研究生创新专项资金(YC2018093)
Foundation items:National Natural Science Foundation of China (61762065, 61363015, 61262020); Natural Science Foundation of Jiangxi Province, China (20171ACB20018, 20171BAB202009, 20171BBH80022); Innovation Foundation for Postgraduate Student of Jiangxi Province (YC2018093)
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舒坚,马玉良,林伟杰,刘琳岚.一种基于节点行为模式的相似性指标.软件学报,2018,29(S1):92-104

SHU Jian,MA Yu-Liang,LIN Wei-Jie,LIU Lin-Lan.Similarity Index Based on Node Behavior Patterns.Journal of Software,2018,29(S1):92-104