A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
With the proliferation of wireless communication devices integrating GPS technology, trajectory datasets are becoming more and more available. The problems concerning the transmission and the storage of such data have become prominent with the continuous increase in volume of these data. A few works in the field of moving object databases deal with spatio-temporal compression. However, these works only consider the case of objects moving freely in the space. In this paper, we tackle the problemdoi:10.1007/s10707-014-0208-4 fatcat:z5efnrabkzahnofg2bp2jpm22m
more »... of compressing trajectory data in road networks with deterministic error bounds. We analyze the limitations of the existing methods and data models for road network trajectory compression. Then, we propose an extended data model and a network partitioning algorithm into long paths to increase the compression rates for the same error bound. We integrate these proposals with the state-of-the-art Douglas-Peucker compression algorithm to obtain a new technique to compress road network trajectory data with deterministic error bounds. The extensive experimental results confirm the appropriateness of the proposed approach that exhibits compression rates close to the ideal ones with respect to the employed Douglas-Peucker compression algorithm.
Personal Data Management Systems (PDMS) advance at a rapid pace allowing us to integrate all our personal data in a single place and use it for our benefit and for the benefit of the community. This leads to a significant paradigm shift since personal data become massively distributed and opens an important question: how to query this massively distributed data in an efficient, pertinent and privacy preserving way? This demonstration proposes a fully-distributed PDMS called DISPERS, built ondoi:10.14778/3352063.3352091 fatcat:ghjbdprgczcijkljyvflpc7foq
more »... of SEP2P, allowing users to securely and efficiently share and query their personal data. The demonstration platform graphically illustrates the query execution in details, showing that DISPERS leads to maximal system security with low and scalable overhead. Attendees are welcome to challenge the security provided by DISPERS using the proposed hacking tools.
The Personal Cloud paradigm has emerged as a solution that allows individuals to manage under their control the collection, usage and sharing of their data. However, by regaining the full control over their data, the users also inherit the burden of protecting it against all forms of attacks and abusive usages. The Secure Personal Cloud architecture relieves the individual from this security task by employing a secure token (i.e., a tamper-resistant hardware device) to control all the sensitivedoi:10.1016/j.is.2017.09.003 fatcat:tbjpna23drdsvbco7wgc3v6dpa
more »... information (e.g., encryption keys, metadata, indexes) and operations (e.g., authentication, data encryption/decryption, access control, and query processing). However, secure tokens are usually equipped with extremely low RAM but have significant Flash storage capacity (Gigabytes), which raises important barriers for embedded data management. This paper presents a new embedded search engine specifically designed for secure tokens, which applies to the important use-case of managing and securing documents in the Personal Cloud context. Conventional search engines privilege either insertion or query scalability but cannot meet both requirements at the same time. Moreover, very few solutions support data deletions and updates in this context. In this paper, we introduce three design principles, namely Write-Once Partitioning, Linear Pipelining and Background Linear Merging, and show how they can be combined to produce an embedded search engine matching the hardware constraints of secure tokens and reconciling high insert/delete/update rate and query scalability. Our experimental results, obtained with a prototype running on a representative hardware platform, demonstrate the scalability of the approach on large datasets and its superiority compared to state of the art methods. Finally, we also discuss the integration of our solution in another important real usecase related to performing information retrieval in smart objects.
Mobile participatory sensing could be used in many applications such as vehicular traffic monitoring, pollution tracking, or even health surveying. However, its success depends on finding a solution for querying large numbers of users which protects user location privacy and works in realtime. This paper presents PAMPAS, a privacy-aware mobile distributed system for efficient data aggregation in mobile participatory sensing. In PAMPAS, mobile devices enhanced with secure hardware, called securedoi:10.1145/2949689.2949704 dblp:conf/ssdbm/ThatPZB16 fatcat:p4fl4n3c7bfpfngesehuv27tri
more »... probes (SPs), perform distributed query processing, while preventing users from accessing other users' data. A supporting server infrastructure (SSI) coordinates the inter-SP communication and the computation tasks executed on SPs. PAMPAS ensures that SSI cannot link the location reported by SPs to the user identities even if SSI has additional background information. In addition to its novel system architecture, PAMPAS also proposes two new protocols for privacy-aware location-based aggregation and adaptive spatial partitioning of SPs that work efficiently on resourceconstrained SPs. Our experimental results and security analysis demonstrate that these protocols are able to collect the data, aggregate them, and share statistics or derived models in real-time, without any location privacy leakage.
In this paper, we propose a simple generic model to manage time series. A time series is composed of a calendar with a typed value for each calendar entry. Although the model could support any kind of XML typed values, in this paper we focus on real numbers, which are the usual application. We define basic vector space operations (plus, minus, scale), and also relational-like and application oriented operators to manage time series. We show the interest of this generic model on twoarXiv:1006.0576v1 fatcat:ielxk7ztbjbohjcur7v72jjvcm
more »... (i) a stock investment helper; (ii) an ecological transport management system. Stock investment requires window-based operations while trip management requires complex queries. The model has been implemented and tested in PHP, Java, and XQuery. We show benchmark results illustrating that the computing of 5000 series of over 100.000 entries in length - common requirements for both applications - is difficult on classical centralized PCs. In order to serve a community of users sharing time series, we propose a P2P implementation of time series by dividing them in segments and providing optimized algorithms for operator expression computation.
Traffic congestion causes driver frustration and costs billions of dollars annually in lost time and fuel consumption. This paper presents five traffic rerouting strategies designed to be incorporated in a cost-effective and easily deployable vehicular traffic guidance system that reduces travel time. The proposed strategies proactively compute individually tailored rerouting guidance to be pushed to vehicles when signs of congestion are observed on their route. The five proposed strategies aredoi:10.1109/tvt.2013.2260422 fatcat:5atsjfigzbc23hwb2wijcutb7y
more »... the dynamic shortest path (DSP), the A * shortest path with repulsion (AR * ), the random k shortest path (RkSP), the entropy-balanced kSP (EBkSP), and the flow-balanced kSP (FBkSP). Extensive simulation results show that the proposed strategies are capable of reducing the travel time as much as a state-of-the-art dynamic traffic assignment (DTA) algorithm while avoiding the issues that make DTA impractical, such as the lack of scalability and robustness, and high computation time. Furthermore, the variety of proposed strategies allows tuning the system to different levels of tradeoffs between rerouting effectiveness and computational efficiency. In addition, the proposed traffic guidance system can significantly improve the traffic even if many drivers ignore the guidance or if the system adoption rate is relatively low.
This paper presents a new embedded search engine designed for smart objects. Such devices are generally equipped with extremely low RAM and large Flash storage capacity. To tackle these conflicting hardware constraints, conventional search engines privilege either insertion or query scalability but cannot meet both requirements at the same time. Moreover, very few solutions support document deletions and updates in this context. In this paper, we introduce three design principles, namelydoi:10.14778/2777598.2777600 fatcat:u7jpwitacrbgvfenjg56byg2t4
more »... nce Partitioning, Linear Pipelining and Background Linear Merging, and show how they can be combined to produce an embedded search engine reconciling high insert/delete/update rate and query scalability. We have implemented our search engine on a development board having a hardware configuration representative for smart objects and have conducted extensive experiments using two representative datasets. The experimental results demonstrate the scalability of the approach and its superiority compared to state of the art methods.
Sandu Popa is with the Department of Computer Science, University of Versailles Saint-Quentin-en-Yvelines, Versailles 78000, France, and also with Inria Paris-Rocquencourt, Le Chesnay 78145, France (e-mail ... : firstname.lastname@example.org). and to receive location updates) in real-time. ...doi:10.1109/tmc.2016.2538226 fatcat:b6ms4lov6ncmflmculw5ntin5a
The emerging Personal Could paradigm holds the promise of a Privacy-by-Design storage and computing platform where personal data remain under the individual's control while being shared by valuable applications. However, leaving the data management control to user's hands pushes the security issues to the user's platform. This demonstration presents a Secure Personal Cloud Platform relying on a query and access control engine embedded in a tamper resistant hardware device connected to thedoi:10.1145/2723372.2735376 dblp:conf/sigmod/LallaliAPP15 fatcat:aebkt7eignhjbdlr3is2jy75xe
more »... platform. The main difficulty lies in the design of an inverted document index and its related search and update algorithms capable of tackling the strong hardware constraints of these devices. We have implemented our engine on a real tamper resistant hardware device and present its capacity to regulate the access to a personal dataspace. The objective of this demonstration is to show (1) that secure hardware is a key enabler of the Personal Cloud paradigm and (2) that new embedded indexing and querying techniques can tackle the hardware constraints of tamper-resistant devices and provide scalable solutions for the Personal Cloud.
Nous avons présenté à la conférence SAGEO en 2008 une version préliminaire de ce travail (Sandu Popa et al., 2008a) . ... Nous avons pu montrer une application réelle d'analyse de conduite naturelle en liaison avec les systèmes de transports intelligents (Sandu Popa et al., 2008b) et les résultats sont prometteurs pour ...doi:10.3166/isi.14.5.35-58 fatcat:j6l2k4zqujbmplzftpsxf3stva
In this paper we propose PARINET, a new access method to efficiently retrieve the trajectories of objects moving in networks. The structure of PARINET is based on a combination of graph partitioning and a set of composite B + -tree local indexes. PARINET is designed for historical data and relies on the distribution of the data over the network as for historical data, the data distribution is known in advance. Because the network can be modeled using graphs, the partitioning of the trajectorydoi:10.1109/icde.2010.5447885 dblp:conf/icde/PopaZOBV10 fatcat:dji552p4v5g55h7prxzef5ib7m
more »... ta is based on graph partitioning theory and can be tuned for a given query load. The data in each partition is indexed on the time component using B + -trees. We study different types of queries, and provide an optimal configuration for several scenarios. PARINET can easily be integrated into any RDBMS, which is an essential asset particularly for industrial or commercial applications. The experimental evaluation under an off-the-shelf DBMS shows that PARINET is robust. It also significantly outperforms both MON-tree and another R-tree based access method which are the reference indexing techniques for in-network trajectory databases.
Spatial data mining is an active topic in spatial databases. This paper proposes a new clustering method for moving object trajectories databases. It applies specifically to trajectories that only lie on a predefined network. The proposed algorithm (NETSCAN) is inspired from the wellknown density based algorithms. However, it takes advantage of the network constraint to estimate the object density. Indeed, NETSCAN first computes dense paths in the network based on the moving object count, then,doi:10.1007/978-3-540-68566-1_36 fatcat:bwdy3zmlxjggdmrvetm23nhkfq
more »... it clusters the sub-trajectories which are similar to the dense paths. The user can adjust the clustering result by setting a density threshold for the dense paths, and a similarity threshold within the clusters. This paper describes the proposed method. An implementation is reported, along with experimental results that show the effectiveness of our approach and the flexibility allowed by the user parameters.
Erich Schröger-Leipzig University, Institute of Psychology ORGANIZING COMMITTEE Presidents PhD Mihai Anitei PhD Lucian Ciolan PhD Viorel Iulian Tanase PhD Ana Maria Marhan Members PhD Mihaela Chraif PhD ... Daniela PhD Roxana Urea PhD student Ion Bucur PhD student Ana Maria Cazan PhD student Catalina Cicei PhD student Barbara Craciun PhD student Aliodor Manolea PhD student Cristian Manea PhD student Radu Popa ...doi:10.1016/j.sbspro.2013.05.004 fatcat:4nuq74mtg5aj3jsde4svfvfdmq
The fifth paper, "Mobile Participatory Sensing with Strong Privacy Guarantees Using Secure Probes", by Iulian Sandu Popa, Dai Hai Ton That, Karine Zeitouni, Cristian Borcea, presents PAMPAS, a privacy-aware ...doi:10.1007/s10707-021-00432-3 fatcat:a5zryjzsr5glvostgm4w7gcefi
The VLDB journal
The paper Indexing in-Network Trajectory Flows, by Iulian Sandu Popa, Karine Zeitouni, Vincent Oria, Dominique Barth, and Sandrine Vial, proposes a new access method for the efficient retrieval of objects ...doi:10.1007/s00778-011-0250-x fatcat:syidvlat35h3vliureceixmivy
« Previous Showing results 1 — 15 out of 56 results