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Conference

Mobile Data Management 

About: Mobile Data Management is an academic conference. The conference publishes majorly in the area(s): Mobile computing & Wireless sensor network. Over the lifetime, 1430 publications have been published by the conference receiving 24984 citations.


Papers
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Book ChapterDOI
08 Jan 2001
TL;DR: This paper defines the concept of sensor databases mixing stored data represented as relations and sensorData represented as time series, and describes the design and implementation of the COUGAR sensor database system.
Abstract: Sensor networks are being widely deployed for measurement, detection and surveillance applications. In these new applications, users issue long-running queries over a combination of stored data and sensor data. Most existing applications rely on a centralized system for collecting sensor data. These systems lack flexibility because data is extracted in a predefined way; also, they do not scale to a large number of devices because large volumes of raw data are transferred regardless of the queries that are submitted. In our new concept of sensor database system, queries dictate which data is extracted from the sensors. In this paper, we define the concept of sensor databases mixing stored data represented as relations and sensor data represented as time series. Each long-running query formulated over a sensor database defines a persistent view, which is maintained during a given time interval. We also describe the design and implementation of the COUGAR sensor database system.

763 citations

Journal ArticleDOI
01 Jul 1999
TL;DR: The update problem is to determine when the location of a moving object in the database (namely its database location) should be updated, and an information cost model is proposed that captures uncertainty, deviation, and communication.
Abstract: In this paper, we consider databases representing information about moving objects (e.g., vehicles), particularly their location. We address the problems of updating and querying such databases. Specifically, the update problem is to determine when the location of a moving object in the database (namely its database location) should be updated. We answer this question by proposing an information cost model that captures uncertainty, deviation, and communication. Then we analyze dead-reckoning policies, namely policies that update the database location whenever the distance between the actual location and the database location exceeds a given threshold, x. Dead-reckoning is the prevalent approach in military applications, and our cost model enables us to determine the threshold x. We propose several dead-reckoning policies and we compare their performance by simulation. Then we consider the problem of processing range queries in the database. An example of a range query is ‘retrieve the objects that are currently inside a given polygon P′. We propose a probabilistic approach to solve the problem. Namely, the DBMS will answer such a query with a set of objects, each of which is associated with a probability that the object is inside P.

447 citations

Proceedings ArticleDOI
01 May 2007
TL;DR: The global sensor networks (GSN) middleware is described, its conceptual model, abstractions, and architecture are presented, and the efficiency of the implementation is demonstrated through experiments with typical high-load application profiles.
Abstract: With the price of wireless sensor technologies diminishing rapidly we can expect large numbers of autonomous sensor networks being deployed in the near future. These sensor networks will typically not remain isolated but the need of interconnecting them on the network level to enable integrated data processing will arise, thus realizing the vision of a global "sensor Internet." This requires a flexible middleware layer which abstracts from the underlying, heterogeneous sensor network technologies and supports fast and simple deployment and addition of new platforms, facilitates efficient distributed query processing and combination of sensor data, provides support for sensor mobility, and enables the dynamic adaption of the system configuration during runtime with minimal (zero-programming) effort. This paper describes the global sensor networks (GSN) middleware which addresses these goals. We present GSN's conceptual model, abstractions, and architecture, and demonstrate the efficiency of the implementation through experiments with typical high-load application profiles. The GSN implementation is available from http://gsn.sourceforge.net/.

373 citations

Proceedings ArticleDOI
23 May 2010
TL;DR: This work proposes an Interactive Voting-based Map Matching (IVMM) algorithm that does not only consider the spatial and temporal information of a GPS trajectory but also devise a voting-based strategy to model the weighted mutual influences between GPS points.
Abstract: Matching a raw GPS trajectory to roads on a digital map is often referred to as the Map Matching problem. However, the occurrence of the low-sampling-rate trajectories (e.g. one point per 2 minutes) has brought lots of challenges to existing map matching algorithms. To address this problem, we propose an Interactive Voting-based Map Matching (IVMM) algorithm based on the following three insights: 1) The position context of a GPS point as well as the topological information of road networks, 2) the mutual influence between GPS points (i.e., the matching result of a point references the positions of its neighbors; in turn, when matching its neighbors, the position of this point will also be referenced), and 3) the strength of the mutual influence weighted by the distance between GPS points (i.e., the farther distance is the weaker influence exists). In this approach, we do not only consider the spatial and temporal information of a GPS trajectory but also devise a voting-based strategy to model the weighted mutual influences between GPS points. We evaluate our IVMM algorithm based on a user labeled real trajectory dataset. As a result, the IVMM algorithm outperforms the related method (ST-Matching algorithm).

315 citations

Proceedings ArticleDOI
24 Aug 2004
TL;DR: This paper proposes a prediction-based energy saving scheme, called PES, to reduce the energy consumption for object tracking under acceptable conditions, and compares PES against the basic schemes proposed in the paper to explore the conditions under which PES is most desired.
Abstract: In order to fully realize the potential of sensor networks, energy awareness should be incorporated into every stage of the network design and operation. In this paper, we address the energy management issue in a sensor network killer application - object tracking sensor networks (OTSNs). Based on the fact that the movements of the tracked objects are sometimes predictable, we propose a prediction-based energy saving scheme, called PES, to reduce the energy consumption for object tracking under acceptable conditions. We compare PES against the basic schemes we proposed in the paper to explore the conditions under which PES is most desired. We also test the effect of some parameters related to the system workload, object moving behavior and sensing operations on PES through extensive simulation. Our results show that PES can save significant energy under various conditions.

313 citations

Performance
Metrics
No. of papers from the Conference in previous years
YearPapers
202146
202059
2019101
201845
201759
201669