2014 IEEE 15th International Conference on Mobile Data Management最新文献_第7页

Top-k Query Processing and Malicious Node Identification against Data Replacement Attack in MANETs 面向多网数据替换攻击的Top-k查询处理及恶意节点识别

2014 IEEE 15th International Conference on Mobile Data Management Pub Date : 2014-07-14 DOI: 10.1109/MDM.2014.40

Takuji Tsuda, Yuka Komai, Yuya Sasaki, T. Hara, S. Nishio

{"title":"Top-k Query Processing and Malicious Node Identification against Data Replacement Attack in MANETs","authors":"Takuji Tsuda, Yuka Komai, Yuya Sasaki, T. Hara, S. Nishio","doi":"10.1109/MDM.2014.40","DOIUrl":"https://doi.org/10.1109/MDM.2014.40","url":null,"abstract":"In mobile ad hoc networks (MANETs), it is effective for mobile nodes to retrieve data items using top-k queries, in which data items are ordered according to a particular attribute score, and the query-issuing node acquires the data items with the k highest scores. However, accurate results may not be acquired in environments where malicious nodes are present. In top-k queries, it is important to neutralize attacks in which malicious nodes attempt to replace necessary data items with unnecessary ones (we call these, data replacement attacks). In this paper, we propose methods for top-k query processing and malicious node identification against data replacement attack in MANETs. In the top-k query processing method, in order to maintain accuracy of the query result, nodes reply with data items with the k highest scores, along multiple routes. Moreover, to enable detection of data replacement attacks, reply messages include information on the route along which reply messages are forwarded, and thus the query-issuing node can know the data items that properly belong to the message. In the malicious node identification method, the query-issuing node first narrows down the malicious node candidates, using the received message information, and then requests information on the data items sent by these candidates. In this way, the query-issuing node can identify the malicious node. Finally, we verify, through simulation experiments, that the proposed top-k query processing method achieves high accuracy of the query result, and that the malicious node identification method effectively identifies a malicious node.","PeriodicalId":322071,"journal":{"name":"2014 IEEE 15th International Conference on Mobile Data Management","volume":"34 44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116215033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Cost-Efficient Spatial Network Partitioning for Distance-Based Query Processing 基于距离查询处理的高效空间网络分区

2014 IEEE 15th International Conference on Mobile Data Management Pub Date : 2014-07-01 DOI: 10.1109/MDM.2014.8

Jiping Wang, Kai Zheng, Hoyoung Jeung, Haozhou Wang, Bolong Zheng, Xiaofang Zhou

{"title":"Cost-Efficient Spatial Network Partitioning for Distance-Based Query Processing","authors":"Jiping Wang, Kai Zheng, Hoyoung Jeung, Haozhou Wang, Bolong Zheng, Xiaofang Zhou","doi":"10.1109/MDM.2014.8","DOIUrl":"https://doi.org/10.1109/MDM.2014.8","url":null,"abstract":"The efficiency of spatial query processing is crucial for many applications such as location-based services. In spatial networks, queries like k-NN queries are all based on network distance evaluation. Classic solutions for these queries rely on network expansion and are not efficient enough for large networks. Some approaches have improved the query efficiency but brought considerable space cost for index. To address these problems, we propose a hierarchical graph partitioning based index named Partition Tree. It organizes the vertices of a spatial network into a hierarchy through a series of graph partitioning processes. Meanwhile precomputed distances are associated with this hierarchy to facilitate efficient query processing. Inspired by the observation that queries are usually invoked around objects of interest, we propose a query-oriented optimization on top of the Partition Tree. It uses a cost model to evaluate the influence of the object distribution and partitioning topology on the query efficiency. Then a cost-efficient graph partitioning method is developed based on this cost model. Experimental results on real datasets demonstrate that our proposed index and algorithms have superior performance over the state-of-the-art approaches and are scalable to large spatial networks.","PeriodicalId":322071,"journal":{"name":"2014 IEEE 15th International Conference on Mobile Data Management","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128311837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Social-Aware Top-k Spatial Keyword Search 社会意识的Top-k空间关键字搜索

2014 IEEE 15th International Conference on Mobile Data Management Pub Date : 2014-07-01 DOI: 10.1109/MDM.2014.35

Dingming Wu, Yafei Li, Byron Choi, Jianliang Xu

引用次数: 29

Oscillation Resolution for Mobile Phone Cellular Tower Data to Enable Mobility Modelling 移动电话蜂窝塔数据的振荡分辨率以实现移动建模

2014 IEEE 15th International Conference on Mobile Data Management Pub Date : 2014-07-01 DOI: 10.1109/MDM.2014.46

Wei Wu, Yue Wang, J. Gomes, D. Anh, S. Antonatos, Mingqiang Xue, Peng Yang, Ghim-Eng Yap, Xiaoli Li, S. Krishnaswamy, James Decraene, A. Nash

{"title":"Oscillation Resolution for Mobile Phone Cellular Tower Data to Enable Mobility Modelling","authors":"Wei Wu, Yue Wang, J. Gomes, D. Anh, S. Antonatos, Mingqiang Xue, Peng Yang, Ghim-Eng Yap, Xiaoli Li, S. Krishnaswamy, James Decraene, A. Nash","doi":"10.1109/MDM.2014.46","DOIUrl":"https://doi.org/10.1109/MDM.2014.46","url":null,"abstract":"One major problem of using location data collected from mobile cellular networks for mobility modelling is the oscillation phenomenon. An oscillation occurs when a mobile phone intermittently switches between cell towers instead of connecting to the nearest cell tower. For the purpose of mobility modeling, the location data needs to be cleansed to approximate the mobile device's actual location. However, this constitutes a challenge because the mobile device's true location is not known. In this paper, we study the oscillation resolution problem. We propose an algorithm framework called DECRE (Detect, Expand, Check, Remove) to detect and remove oscillation logs. To make informed decisions DECRE includes four steps: Detect, to identify log sequences that may contain oscillation using a few heuristics based on the concepts of stable period and moving at impossible speed, Expand, to look before and after suspicious records to gain more information, Check, to check whether a cell tower is observed repeatedly (which is a strong indication of oscillation), and Remove, resolving oscillation by selecting a cell tower to approximate the mobile device's actual location. Our experimental results on travel diaries show that our oscillation resolution approach is able to remove records that are far from mobile device's ground-truth locations, improve the quality of the location data, and performs better than an existing method. Our performance study on large scale cell tower data shows that the MapReduce implementation of our approach is able to process 1 Terabyte of cell tower data in five hours using a small cluster.","PeriodicalId":322071,"journal":{"name":"2014 IEEE 15th International Conference on Mobile Data Management","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120924350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 44

A Clustering Approach to the Discovery of Points of Interest from Geo-Tagged Microblog Posts 地理标记微博中兴趣点发现的聚类方法

2014 IEEE 15th International Conference on Mobile Data Management Pub Date : 2014-07-01 DOI: 10.1109/MDM.2014.28

Anders Skovsgaard, Darius Sidlauskas, Christian S. Jensen

{"title":"A Clustering Approach to the Discovery of Points of Interest from Geo-Tagged Microblog Posts","authors":"Anders Skovsgaard, Darius Sidlauskas, Christian S. Jensen","doi":"10.1109/MDM.2014.28","DOIUrl":"https://doi.org/10.1109/MDM.2014.28","url":null,"abstract":"Points of interest (PoI) data serves an important role as a foundation for a wide variety of location-based services. Such data is typically obtained from an authoritative source or from users through crowd sourcing. It can be costly to maintain an up-to-date authoritative source, and data obtained from users can vary greatly in coverage and quality. We are also witnessing a proliferation of both GPS-enabled mobile devices and geotagged content generated by users of such devices. This state of affairs motivates the paper's proposal of techniques for the automatic discovery of PoI data from geo-tagged microblog posts. Specifically, the paper proposes a new clustering technique that takes into account both the spatial and textual attributes of microblog posts to obtain clusters that represent PoIs. The technique expands clusters based on a proposed quality function that enables clusters of arbitrary shape and density. An empirical study with a large database of real geo-tagged microblog posts offers insight into the properties of the proposed techniques and suggests that they are effective at discovering real-world points of interest.","PeriodicalId":322071,"journal":{"name":"2014 IEEE 15th International Conference on Mobile Data Management","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121438079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Handling False Negatives in Indoor RFID Data 处理室内RFID数据中的假阴性

2014 IEEE 15th International Conference on Mobile Data Management Pub Date : 2014-07-01 DOI: 10.1109/MDM.2014.21

A. Baba, Hua Lu, T. Pedersen, Xike Xie

{"title":"Handling False Negatives in Indoor RFID Data","authors":"A. Baba, Hua Lu, T. Pedersen, Xike Xie","doi":"10.1109/MDM.2014.21","DOIUrl":"https://doi.org/10.1109/MDM.2014.21","url":null,"abstract":"The Radio-Frequency Identification (RFID) is a useful technology for object tracking and monitoring systems in indoor environments, e.g., Airport baggage tracking. Nevertheless, the data produced by RFID tracking is inherently uncertain and contains errors. In order to support meaningful high-level applications including queries and analyses over RFID data, it is necessary to cleanse raw RFID data. In this paper, we focus on false negatives in raw indoor RFID tracking data. False negatives occur when a moving object passes the detection range of an RFID reader but the reader fails to produce any readings. We investigate the topology of indoor spaces as well as the deployment of RFID readers, and propose the transition probabilities that capture how likely objects move from one RFID reader to another. We organize such probabilities, together with the characteristics of indoor topology and RFID readers, into a probabilistic distance-aware graph. With the aid of this graph, we design algorithms to identify false negatives and recover missing information in indoor RFID tracking data. We evaluate the proposed cleansing approach using both real and synthetic datasets. The experimental results show that the approach is effective, efficient and scalable.","PeriodicalId":322071,"journal":{"name":"2014 IEEE 15th International Conference on Mobile Data Management","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123142137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 22

Human Mobility Prediction and Unobstructed Route Planning in Public Transport Networks 公共交通网络中的人员流动预测与无障碍路线规划

2014 IEEE 15th International Conference on Mobile Data Management Pub Date : 2014-07-01 DOI: 10.1109/MDM.2014.66

Shuo Shang, Danhuai Guo, Jiajun Liu, Kuien Liu

{"title":"Human Mobility Prediction and Unobstructed Route Planning in Public Transport Networks","authors":"Shuo Shang, Danhuai Guo, Jiajun Liu, Kuien Liu","doi":"10.1109/MDM.2014.66","DOIUrl":"https://doi.org/10.1109/MDM.2014.66","url":null,"abstract":"With the increasing availability of human-tracking data (e.g., Public transport IC card data, trajectory data, etc.), human mobility prediction is increasingly important. In this paper, we study a novel problem of using human-tracking data to predict human mobility and to detect over-crowded stations in public transport networks, and then finding unobstructed routes to go around these over-crowded stations. We believe that this study can bring significant benefits to users in many popular mobile applications such as route planning and recommendation, urban computing, and location based services in general. This problem is challenged by two difficulties: (1) how to detect crowded stations effectively, and (2) how to find unobstructed routes in public transport networks efficiently. To overcome these difficulties, we propose three human-mobility prediction methods based on uniform distribution, standard normal distribution, and priority ranking, respectively, to predict human mobility and to detect over-crowded stations. Then, we develop an efficient algorithm based on network expansion to find unobstructed routes in public transport networks. The performance of the developed algorithms has been verified by extensive experiments.","PeriodicalId":322071,"journal":{"name":"2014 IEEE 15th International Conference on Mobile Data Management","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123523229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 23

An Interactive Analytics Tool for Understanding Location Semantics and Mobility of Users Using Mobile Network Data 使用移动网络数据理解位置语义和用户移动性的交互式分析工具

2014 IEEE 15th International Conference on Mobile Data Management Pub Date : 2014-07-01 DOI: 10.1109/MDM.2014.50

M. Dash, G. G. Chua, Hai-Long Nguyen, Ghim-Eng Yap, Hong Cao, X. Li, S. Krishnaswamy, James Decraene, A. Nash

{"title":"An Interactive Analytics Tool for Understanding Location Semantics and Mobility of Users Using Mobile Network Data","authors":"M. Dash, G. G. Chua, Hai-Long Nguyen, Ghim-Eng Yap, Hong Cao, X. Li, S. Krishnaswamy, James Decraene, A. Nash","doi":"10.1109/MDM.2014.50","DOIUrl":"https://doi.org/10.1109/MDM.2014.50","url":null,"abstract":"Knowledge about population distribution of planning areas helps in making urban development decisions. Two important criteria are: \"where do people live?\" and \"where do they work?\" In this paper we propose methods to find home and workplaces from mobile network data. Home and work places are essential for discovery of mobility profiles of users. Validation of home and workplace prediction is not straight forward. We validate our methods using correlation with external data. Validation results show that even though a single cellular provider has only a portion of the entire population as its users, distribution of home and work places predicted using its mobile network data match that of government statistics. On the basis of this matching, we can have faith in distributions of more difficult statistics extracted from mobile network data which are difficult to obtain from external sources. We implemented an interactive system to show various distributions such as people living and working in different planning areas, and people working in different job sectors such as manufacturing. Interesting relationships are found by calculating joint distributions, e.g., Where do people, living in a planning area, work, and vice versa. Planning areas are ranked by the average distance traveled from home to work. Another interesting fact we extract is balance. Balance of a planning area is high if people live and work there, it is low if people living in a planning area work in other planning areas. We extend these statistics to regions which consist of many planning areas. The goal of this interactive system is to understand location semantics and mobility of users to aid in making urban development decisions. A video recording with subtitles is uploaded in http://www.youtube.com/watch?v=mo-7-DsCymw.","PeriodicalId":322071,"journal":{"name":"2014 IEEE 15th International Conference on Mobile Data Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129211673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4