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2015 16th IEEE International Conference on Mobile Data Management最新文献

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Mobile Data Management in Indoor Spaces 室内空间移动数据管理
2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.32
C. Laoudias, D. Zeinalipour-Yazti
{"title":"Mobile Data Management in Indoor Spaces","authors":"C. Laoudias, D. Zeinalipour-Yazti","doi":"10.1109/MDM.2015.32","DOIUrl":"https://doi.org/10.1109/MDM.2015.32","url":null,"abstract":"This advanced seminar presents the fundamental mobile data management concepts behind the realization of innovative indoor information services that deal with all aspects of handling indoor data as a valuable resource, including data modeling, data acquisition, query processing, privacy and energy consumption. The goal is to provide an overview of the emerging field of indoor data management with a particular emphasis on mobile systems. We tackle the topic from a wide range of perspectives: fundamentals, definitions, current state, academic & industrial perspective, reality & visionary scenarios as well as future challenges. The seminar captures the big picture, such that interested researchers and practitioners can expand their study by following the references. Our presentation will be carried out through the lens of an experimental Indoor Information System we developed at the University of Cyprus, coined Anyplace, which has obtained three international awards and was ranked the second most accurate indoor localization technology by Microsoft Research at IEEE/ACM IPSN'14.","PeriodicalId":187331,"journal":{"name":"2015 16th IEEE International Conference on Mobile Data Management","volume":"3 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":"125974456","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
SensePresence: Infrastructure-Less Occupancy Detection for Opportunistic Sensing Applications SensePresence:机会感测应用的无基础设施占用检测
2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.41
Md Abdullah Al Hafiz Khan, H. S. Hossain, Nirmalya Roy
{"title":"SensePresence: Infrastructure-Less Occupancy Detection for Opportunistic Sensing Applications","authors":"Md Abdullah Al Hafiz Khan, H. S. Hossain, Nirmalya Roy","doi":"10.1109/MDM.2015.41","DOIUrl":"https://doi.org/10.1109/MDM.2015.41","url":null,"abstract":"Predicting the occupancy related information in an environment has been investigated to satisfy the myriad requirements of various evolving pervasive, ubiquitous, opportunistic and participatory sensing applications. Infrastructure and ambient sensors based techniques have been leveraged largely to determine the occupancy of an environment incurring a significant deployment and retrofitting costs. In this paper, we advocate an infrastructure-less zero-configuration multimodal smartphone sensor-based techniques to detect fine-grained occupancy information. We propose to exploit opportunistically smartphones' acoustic sensors in presence of human conversation and motion sensors in absence of any conversational data. We develop a novel speaker estimation algorithm based on unsupervised clustering of overlapped and non-overlapped conversational data to determine the number of occupants in a crowded environment. We also design a hybrid approach combining acoustic sensing opportunistically with locomotive model to further improve the occupancy detection accuracy. We evaluate our algorithms in different contexts, conversational, silence and mixed in presence of 10 domestic users. Our experimental results on real-life data traces collected from 10 occupants in natural setting show that using this hybrid approach we can achieve approximately 0.76 error count distance for occupancy detection accuracy on average.","PeriodicalId":187331,"journal":{"name":"2015 16th IEEE International Conference on Mobile Data Management","volume":"56 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":"126274106","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: 19
Towards a Microblogs Data Management System 微博数据管理系统的实现
2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.24
A. Magdy, M. Mokbel
{"title":"Towards a Microblogs Data Management System","authors":"A. Magdy, M. Mokbel","doi":"10.1109/MDM.2015.24","DOIUrl":"https://doi.org/10.1109/MDM.2015.24","url":null,"abstract":"This paper advocates for the need to build a Microblogs Data Management System (MDMS) as an end-to-end data management system to support indexing, querying, and analyzing microblogs, e.g., Tweets, comments, or check-in's. We identify a set of characteristics for microblogging environments that are distinguishing from any other data management environment. Then, we propose a system architecture for the first Microblogs Data Management System, which includes indexing, querying, and recovery components. The indexing component is responsible for indexing recent data in memory, indexing older data in disk, and synchronizing the flow of data from memory to disk without affecting the query response time. The querying component is responsible for retrieving the query answer from both memory and disk storage as well as employing online selectivity estimation techniques tuned to the behavior of microblogs data. The recovery module allows for efficiently storing and processing incoming microblogs in memory without worrying about data loss.","PeriodicalId":187331,"journal":{"name":"2015 16th IEEE International Conference on Mobile Data Management","volume":"73 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":"132412642","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
Aerial Vehicle Trajectory Design for Task Aggregation 任务聚合的飞行器轨迹设计
2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.38
Amarender Reddy Mekala, S. Madria, M. Linderman
{"title":"Aerial Vehicle Trajectory Design for Task Aggregation","authors":"Amarender Reddy Mekala, S. Madria, M. Linderman","doi":"10.1109/MDM.2015.38","DOIUrl":"https://doi.org/10.1109/MDM.2015.38","url":null,"abstract":"In this demo, an optimal design method for generating a flight path passing through specified waypoints while satisfying the task points sent by the ground base station is proposed. Each specified waypoint is reached exactly at the specified location and time while intermediate waypoints are generated in such a way that they satisfy the task points with high task priority and high QoS priority. Generated waypoints are points from where imagery data of the task points are collected and taking into consideration factors such as task points' priorities, sensory capability and deviation required from the shortest path to satisfy that waypoint aggregates these task points. In this demo paper, we demonstrate the procedure for 4D flight trajectory generation, by taking the velocities, maneuverability of the aerial vehicle into consideration while ensuring that the vehicle avoids no-fly zones.","PeriodicalId":187331,"journal":{"name":"2015 16th IEEE International Conference on Mobile Data Management","volume":"21 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":"132497892","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: 1
Exploring Institution-Based Mobility: Which Universities Attract Athletes from Distant and Diverse Locales? 探索基于制度的流动性:哪些大学吸引来自遥远和不同地区的运动员?
2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.28
Clio Andris, Zoe Andris
{"title":"Exploring Institution-Based Mobility: Which Universities Attract Athletes from Distant and Diverse Locales?","authors":"Clio Andris, Zoe Andris","doi":"10.1109/MDM.2015.28","DOIUrl":"https://doi.org/10.1109/MDM.2015.28","url":null,"abstract":"Institutions are powerful forces in modern society -- they affect human mobility, and are constantly pushing and pulling individuals across geographic space. Institution data is rarely including in studies of mobility, although we find these data to be a rich source of information on human mobility. We visit over 1000 U.S. University athletics web pages from 78 universities, 20 different types of sports, to produce a 90,000+ record dataset of U.S. And international student athletes and their hometowns. This new agent-based origin-destination data set has not been previously gathered into one file for public use. For each university, we measure its \"pull power\", i.e. Its ability to attract students from many different, and distant hometowns. From these data, we explore the mobility of students from different universities and find witch institutions are catalyzing human migration and movement to 'powerful' extents.","PeriodicalId":187331,"journal":{"name":"2015 16th IEEE International Conference on Mobile Data Management","volume":"26 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":"115369850","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
Spatial Predictive Queries 空间预测查询
2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.76
Abdeltawab M. Hendawi, Mohamed H. Ali
{"title":"Spatial Predictive Queries","authors":"Abdeltawab M. Hendawi, Mohamed H. Ali","doi":"10.1109/MDM.2015.76","DOIUrl":"https://doi.org/10.1109/MDM.2015.76","url":null,"abstract":"In this seminar, we address spatial predictive queries both in Euclidian spaces and over road networks. We provide a definition for various types of spatial predictive queries, describe current research trends, and envision future directions. We present practical application scenarios and emphasize the roadblocks that are holding industry back from the commercialization of spatial predictive queries. This seminar targets audience in mobile data management, spatiotemporal query processing, mobile crowd sourcing, and tracking of moving objects.","PeriodicalId":187331,"journal":{"name":"2015 16th IEEE International Conference on Mobile Data Management","volume":"43 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":"114783621","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
iCOMOT -- A Toolset for Managing IoT Cloud Systems iCOMOT—管理物联网云系统的工具集
2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.65
Hong Linh Truong, G. Copil, S. Dustdar, Duc-Hung Le, D. Moldovan, Stefan Nastic
{"title":"iCOMOT -- A Toolset for Managing IoT Cloud Systems","authors":"Hong Linh Truong, G. Copil, S. Dustdar, Duc-Hung Le, D. Moldovan, Stefan Nastic","doi":"10.1109/MDM.2015.65","DOIUrl":"https://doi.org/10.1109/MDM.2015.65","url":null,"abstract":"Developing and operating IoT cloud systems require novel features for deploying, controlling, monitoring and testing both IoT units and cloud services in an integrated environment spanning different infrastructures. In this paper, we demonstrate iCOMOT -- a novel toolset offering these features. Using iCOMOT we can perform various activities, such as dynamically reconfiguration of sensors, communication protocols, and cloud services in an elastic manner, suitable for testing and assuring quality of IoT cloud systems configurations. We will demonstrate our iCOMOT with a real-world predictive maintenance case study.","PeriodicalId":187331,"journal":{"name":"2015 16th IEEE International Conference on Mobile Data Management","volume":"2022 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":"114912083","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: 5
Managing Infrastructure-Based Vehicular Networks 管理基于基础设施的车辆网络
2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.59
C. M. Silva, Wagner Meira Jr
{"title":"Managing Infrastructure-Based Vehicular Networks","authors":"C. M. Silva, Wagner Meira Jr","doi":"10.1109/MDM.2015.59","DOIUrl":"https://doi.org/10.1109/MDM.2015.59","url":null,"abstract":"In this thesis work the authors exploit the management of infrastructure-based vehicular networks. The authors begin to work by investigating the most basic problem faced by the network designers when planning an infrastructure-based vehicular network: given a road network, a flow, and α available RSUs, where the RSUs must be located in order to maximize the network performance? The authors propose a novel approach for locating the RSUs: the authors develop a deployment algorithm based on partial mobility information. By partial mobility information, we mean: i) density of vehicles along the road network; and, ii) migration ratios from distinct locations of the road network.","PeriodicalId":187331,"journal":{"name":"2015 16th IEEE International Conference on Mobile Data Management","volume":"1 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":"129578489","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: 9
Scalable Spatial Crowdsourcing: A Study of Distributed Algorithms 可扩展空间众包:分布式算法研究
2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.55
Abdullah Alfarrarjeh, Tobias Emrich, C. Shahabi
{"title":"Scalable Spatial Crowdsourcing: A Study of Distributed Algorithms","authors":"Abdullah Alfarrarjeh, Tobias Emrich, C. Shahabi","doi":"10.1109/MDM.2015.55","DOIUrl":"https://doi.org/10.1109/MDM.2015.55","url":null,"abstract":"Recently spatial crowd sourcing was introduced as a natural extension to traditional crowd sourcing allowing for tasks to have a geospatial component, i.e., A task can only be performed if a worker is physically present at the location of the task. The problem of assigning spatial tasks to workers in a spatial crowd sourcing system can be formulated as a weighted bipartite b-matching graph problem that can be solved optimally by existing methods for the minimum cost maximum flow problem. However, these methods are still too complex to run repeatedly for an online system, especially when the number of incoming workers and tasks increases. Hence, we propose a class of approaches that utilizes an online partitioning method to reduce the problem space across a set of cloud servers to construct independent bipartite graphs and solve the assignment problem in parallel. Our approaches solve the spatial task assignment approximately but competitive to the exact solution. We experimentally verify that our approximate approaches outperform the centralized and Map Reduce version of the exact approach with acceptable accuracy and thus suitable for online spatial crowd sourcing at scale.","PeriodicalId":187331,"journal":{"name":"2015 16th IEEE International Conference on Mobile Data Management","volume":"1 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":"130792184","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: 41
IGOD -- Identifying Geolocation of Cloud Datacenter Hosting Mobile User's Data IGOD——识别托管移动用户数据的云数据中心的地理位置
2015 16th IEEE International Conference on Mobile Data Management Pub Date : 2015-06-15 DOI: 10.1109/MDM.2015.20
Chetan Jaiswal, Vijay Kumar
{"title":"IGOD -- Identifying Geolocation of Cloud Datacenter Hosting Mobile User's Data","authors":"Chetan Jaiswal, Vijay Kumar","doi":"10.1109/MDM.2015.20","DOIUrl":"https://doi.org/10.1109/MDM.2015.20","url":null,"abstract":"We introduce a novel algorithm called IGOD to identify the geolocation of the cloud data center which is hosting the data of a mobile user. IGOD efficiently geo locate any target data center as accurately as possible and is highly cost-effective. It provides audit control and assurance against the cloud storage providers who may relocate mobile customer's data. We use Planet Lab for our data collection. We compared our approach to the earlier approaches that used Ping delay to predict the geolocation of a target. We claim that IGOD is highly cost-effective.","PeriodicalId":187331,"journal":{"name":"2015 16th IEEE International Conference on Mobile Data Management","volume":"43 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":"125604904","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: 3
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