2015 16th IEEE International Conference on Mobile Data Management最新文献_第2页

Human Mobility Computing and Privacy: Fad or Reality? 人类移动、计算和隐私:时尚还是现实?

2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.86

Adam J. Lee, K. Pelechrinis, D. Zeinalipour-Yazti

{"title":"Human Mobility Computing and Privacy: Fad or Reality?","authors":"Adam J. Lee, K. Pelechrinis, D. Zeinalipour-Yazti","doi":"10.1109/MDM.2015.86","DOIUrl":"https://doi.org/10.1109/MDM.2015.86","url":null,"abstract":"The advent of mobile computing and sensing technologies, in conjunction with omni-present and high-speed mobile networks, allow nowadays the capture of human mobility data at an extremely high fidelity. Modern mobile computing services not only have the capacity to store spatio-temporal mobile data, these nowadays also have the capability to process incoming data in near-real time. As a result, we have a better chance to develop effective strategies and build intelligent systems that play critical roles in areas like public health, traffic engineering, urban planning and economic forecasting. On the other hand, detailed movement data often poses a threat to the privacy and security of users and companies, given that mobile devices are associated with real human custodians. One fundamental question is whether human mobility computing and privacy can co-exist under the same roof, given different cultural, religious, legal, technological and socio-economic backgrounds of societies. This panel will explore how the academia and industry are tackling human mobility computing and privacy challenges at a global scale. It will also identify and debate the key challenges and opportunities, in terms of applications, queries, architectures, to which the mobile data management community should contribute.","PeriodicalId":187331,"journal":{"name":"2015 16th IEEE International Conference on Mobile Data Management","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121207507","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: 0

Converting Mobile Sensing in Data and Data into Action 将移动传感中的数据和数据转化为行动

2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.81

D. Siewiorek, A. Smailagic

引用次数: 0

Vehicle Routing with User-Generated Trajectory Data 车辆路线与用户生成的轨迹数据

2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.29

Vaida Ceikute, Christian S. Jensen

引用次数: 21

Anyplace: A Crowdsourced Indoor Information Service Anyplace:众包室内信息服务

2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.80

Kyriakos Georgiou, Timotheos Constambeys, C. Laoudias, L. Petrou, Georgios Chatzimilioudis, D. Zeinalipour-Yazti

{"title":"Anyplace: A Crowdsourced Indoor Information Service","authors":"Kyriakos Georgiou, Timotheos Constambeys, C. Laoudias, L. Petrou, Georgios Chatzimilioudis, D. Zeinalipour-Yazti","doi":"10.1109/MDM.2015.80","DOIUrl":"https://doi.org/10.1109/MDM.2015.80","url":null,"abstract":"People do most of their activities, business, commerce, entertainment and socializing indoors. As all of these are increasingly aided by online services and indoor spaces are becoming bigger and more complex, there is a growing need for cost-effective indoor localization, mapping, navigation and information services. In this paper, we present a complete Indoor Information Service, coined Anyplace, which has an open, modular, extensible and scalable architecture, making it ideal for a wide range of applications. Our service features three highly desirable properties, namely crowd sourcing, scalability and accuracy. Anyplace implements a set of crowd sourcing-supportive mechanisms to handle the enormous amount of crowd-sensed data, filter incorrect user contributions and exploit Wi-Fi data from heterogeneous mobile devices. Moreover, it uses a big-data architecture for efficient storage and retrieval of localization and mapping data. Finally, our service relies on the abundance of sensory data on smartphones (e.g., Wi-Fi signal strength and inertial measurements) to deliver reliable indoor geolocation information that received several international awards.","PeriodicalId":187331,"journal":{"name":"2015 16th IEEE International Conference on Mobile Data Management","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132472083","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: 24

Predictive Caching Framework for Mobile Wireless Networks 移动无线网络预测缓存框架

2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.14

Sourav Dutta, A. Narang, Souvik Bhattacherjee, A. Das, D. Krishnaswamy

{"title":"Predictive Caching Framework for Mobile Wireless Networks","authors":"Sourav Dutta, A. Narang, Souvik Bhattacherjee, A. Das, D. Krishnaswamy","doi":"10.1109/MDM.2015.14","DOIUrl":"https://doi.org/10.1109/MDM.2015.14","url":null,"abstract":"With increasing popularity of Netflix, Yahoo! Video, etc., interactive multimedia services such as video-on-demand (VoD) provide an interesting and rich field of research. The advent of smarter wireless devices has surged the need for such services through wireless connectivity. However, personalization of individual user needs, reducing latency, coupled with maintaining low operational costs provides a challenging problem. In this paper, we propose an efficient VoD system, for wireless mobile devices, based on a novel caching algorithm, Intelligent Network Caching Algorithm (INCA) using analytics-driven look ahead scheme for both prefetch and replacement policies to deliver higher performance. This enables enhanced Quality Of Experience (QoE) of users with limited infrastructural changes and low operational cost. Alongside, we develop theoretical formulation of the QoE optimization problem that lies at the intersection of MPC (Markov Predictive Control) and MDP (Markov Decision Process). Empirical analysis over realistic user video query logs demonstrate better cache hit rate and QoE with low prefetch bandwidth, compared to existing caching schemes.","PeriodicalId":187331,"journal":{"name":"2015 16th IEEE International Conference on Mobile Data Management","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133221182","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: 6

Comparing Urban Sensing Applications Using Event and Network-Driven Mobile Phone Location Data 比较使用事件和网络驱动的移动电话位置数据的城市传感应用

2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.33

Fabio Pinelli, G. D. Lorenzo, Francesco Calabrese

{"title":"Comparing Urban Sensing Applications Using Event and Network-Driven Mobile Phone Location Data","authors":"Fabio Pinelli, G. D. Lorenzo, Francesco Calabrese","doi":"10.1109/MDM.2015.33","DOIUrl":"https://doi.org/10.1109/MDM.2015.33","url":null,"abstract":"In this paper we address the use of mobile phone location data to build urban sensing applications. In the past decade, several research works have proposed the use of different types of location data from the telecommunication network to characterise people mobility in the city. Thus, several applications to infer urban dynamics where proposed. However, different papers have used different types of mobile phone location data, making it is difficult to understand whether a particular dataset provided by a telecom operator is indeed effective for a specific urban sensing application. In this paper we address this issue by comparing the quality of the insights extracted from different types of mobile phone location data, with specific reference to two urban sensing applications: people count by location, and people flow between locations. Experiments executed on a real dataset provided by a telecom operator in Belgium show the advantages of using network-driven mobile phone location data (collected regardless on whether people are using their phone) compared to the widely used Call Detail Records.","PeriodicalId":187331,"journal":{"name":"2015 16th IEEE International Conference on Mobile Data Management","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116486474","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: 10

Usage of Annotation Tags in the Problem of Mining Similar Users 相似用户挖掘问题中标注标签的使用

2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.83

O. Vedernikov

引用次数: 0

Content Replication in Mobile Vehicular Ad-Hoc Networks 移动车辆自组织网络中的内容复制

2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.56

Fabrício A. Silva, A. Loureiro

{"title":"Content Replication in Mobile Vehicular Ad-Hoc Networks","authors":"Fabrício A. Silva, A. Loureiro","doi":"10.1109/MDM.2015.56","DOIUrl":"https://doi.org/10.1109/MDM.2015.56","url":null,"abstract":"Vehicular ad-hoc network (VANET) is a special type of mobile networks that has received significant attention from the academia and the industry in recent years. VANET applications are emerging as new opportunities for the automobile industry to provide advanced services to connected vehicles and their users. Most of those services, like information, safety, and entertainment systems, require a variety of content to be delivered to vehicles. An useful concept in this case is the one of content replication, which defines that content should be placed close to its potential clients. However, existing replicating solutions, as originally proposed for the Internet, are not suitable to VANETs because of their particular characteristics, such as highly dynamic topology, existence of push-based applications, information-centric nature, location- and time-dependent content, and intermittent connections. Therefore, we propose and evaluate in this work new techniques to replicate content in VANETs that rely on the vehicles' origin-destination (O-D) points. Theresults reveal that our solutions were able to increase the content availability in two case studies, named city-wide and region-wide.","PeriodicalId":187331,"journal":{"name":"2015 16th IEEE International Conference on Mobile Data Management","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115132372","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: 2

A Weighted Distance Similarity Model to Improve the Accuracy of Collaborative Recommender System 一种提高协同推荐系统准确率的加权距离相似模型

2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.43

Bing Huang, Bi-Ru Dai

引用次数: 18

An Interactive Freight-Pooling Service for Efficient Last-Mile Delivery “最后一英里”高效物流互动拼车服务

2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.60

Panagiotis Liakos, A. Delis

引用次数: 15