February 4, 20021 Location Based M-Services Soon there will be more on-line personal mobile devices than on-line stationary PCs. Location based mobile-services.

Slides:



Advertisements
Similar presentations
Fall IM 2000 Evfolution of Presence Based Networks Evolution of Presence Based Networks Jonathan Rosenberg Chief Scientist.
Advertisements

Speedy Agent Car: The Prototype Agent Technology: Final Project Lecturer: Prof. Ho Cheng-Seen Presented by: M Irfan Subakti NTUST, June 7 th 2004.
FindAll: A Local Search Engine for Mobile Phones Aruna Balasubramanian University of Washington.
Constructing Popular Routes from Uncertain Trajectories Ling-Yin Wei 1, Yu Zheng 2, Wen-Chih Peng 1 1 National Chiao Tung University, Taiwan 2 Microsoft.
University of Minnesota 1 / 9 May 2011 Energy-Efficient Location-based Services Mohamed F. Mokbel Department of Computer Science and Engineering University.
CMPT 300: Final Review Chapters 8 – Memory Management: Ch. 8, 9 Address spaces Logical (virtual): generated by the CPU Physical: seen by the memory.
On Reducing Communication Cost for Distributed Query Monitoring Systems. Fuyu Liu, Kien A. Hua, Fei Xie MDM 2008 Alex Papadimitriou.
Boost Write Performance for DBMS on Solid State Drive Yu LI.
Computer Science Spatio-Temporal Aggregation Using Sketches Yufei Tao, George Kollios, Jeffrey Considine, Feifei Li, Dimitris Papadias Department of Computer.
1 SINA: Scalable Incremental Processing of Continuous Queries in Spatio-temporal Databases Mohamed F. Mokbel, Xiaopeng Xiong, Walid G. Aref Presented by.
Approximate querying about the Past, the Present, and the Future in Spatio-Temporal Databases Jimeng Sun, Dimitris Papadias, Yufei Tao, Bin Liu.
INFO 624 Week 3 Retrieval System Evaluation
Aggregation in Sensor Networks NEST Weekly Meeting Sam Madden Rob Szewczyk 10/4/01.
1 Location Information Management and Moving Object Databases “Moving Object Databases: Issues and Solutions” Ouri, Bo, Sam and Liqin.
Dieter Pfoser, LBS Workshop1 Issues in the Management of Moving Point Objects Dieter Pfoser Nykredit Center for Database Research Aalborg University, Denmark.
© Christian S. Jensen - CAMM workshop, Providence, RI, January 24-25, 2002 Data Representation and Indexing in Location-Enabled M-Services Christian S.
1 SINA: Scalable Incremental Processing of Continuous Queries in Spatio-temporal Databases Mohamed F. Mokbel, Xiaopeng Xiong, Walid G. Aref Presented by.
Indexing Spatio-Temporal Data Warehouses Dimitris Papadias, Yufei Tao, Panos Kalnis, Jun Zhang Department of Computer Science Hong Kong University of Science.
Computational Data Modeling and Query Processing in Road Networks Irina Aleksandrova, Augustas Kligys, Laurynas Speičys 4-th WIM meeting, Aalborg 2002.
Trip Planning Queries F. Li, D. Cheng, M. Hadjieleftheriou, G. Kollios, S.-H. Teng Boston University.
TrafficView: A Driver Assistant Device for Traffic Monitoring based on Car-to-Car Communication Sasan Dashtinezhad, Tamer Nadeem Department of CS, University.
Generic Simulator for Users' Movements and Behavior in Collaborative Systems.
Copyright © 2006 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill Technology Education Copyright © 2006 by The McGraw-Hill Companies,
Chapter 1 Database and Database Users Dr. Bernard Chen Ph.D. University of Central Arkansas.
Audumbar Chormale Advisor: Dr. Anupam Joshi M.S. Thesis Defense
Chris Cummings.  Traffic cameras recording targets and retrieving them  Cameras track targets and the data needs to be recorded, but how are you supposed.
Research Area B Leif Kobbelt. Communication System Interface Research Area B 2.
Recommender Systems on the Web: A Model-Driven Approach Gonzalo Rojas – Francisco Domínguez – Stefano Salvatori Department of Computer Science University.
Team Members Abhinav Mishra Amber Palekar Rahul Iyer Vishakha Gupta.
CSC2012 Database Technology & CSC2513 Database Systems.
By Group 6 1. Adaptive Mapping 2 Adaptivity What is adaptivity? “A system is called adaptive if it is able to change its own characteristics automatically.
Database and Database Users. Outline Database Introduction An Example Characteristics of the Database Actors on the Scene Advantages of using the DBMS.
National Datawarehouse for Traffic Information – Big Data supplier Els Rijnierse.
1 Introduction to Database Systems. 2 Database and Database System / A database is a shared collection of logically related data designed to meet the.
Utilities, Customers & SMS Rudi Leitner. Who in this room has a mobile phone? Who in this room has ever sent a text (SMS) message?
1 Synchronizing Outlook and Oracle TCA for Sales Applications February 22, :00 PM – 3:40 PM Presented By Abhinav Raina
1 Wenguang WangRichard B. Bunt Department of Computer Science University of Saskatchewan November 14, 2000 Simulating DB2 Buffer Pool Management.
February 3, Location Based M-Services The numbers of on-line mobile personal devices increase. New types of context-aware e-services become possible.
Machine Learning Approach to Report Prioritization with an Application to Travel Time Dissemination Piotr Szczurek Bo Xu Jie Lin Ouri Wolfson.
Presenter: Mathias Jahnke Authors: M. Zhang, M. Mustafa, F. Schimandl*, and L. Meng Department of Cartography, TU München *Chair of Traffic Engineering.
Copyright © Curt Hill SQL The Intergalactic Standard Database Query Language.
Technical Advisor - Mr. Roni Stern Academic Advisor - Dr. Meir Kelah Members: Shimrit Yacobi Yuval Binenboim Moran Lev Lehman Sharon Shabtai.
Shape-based Similarity Query for Trajectory of Mobile Object NTT Communication Science Laboratories, NTT Corporation, JAPAN. Yutaka Yanagisawa Jun-ichi.
Page 1 Alliver™ Page 2 Scenario Users Contents Properties Contexts Tags Users Context Listener Set of contents Service Reasoner GPS Navigator.
INFORMATION MANAGEMENT Unit 2 SO 4 Explain the advantages of using a database approach compared to using traditional file processing; Advantages including.
Preserving Privacy in GPS Traces via Uncertainty- Aware Path Cloaking Baik Hoh, Marco Gruteser, Hui Xiong, Ansaf Alrabady Presented by Joseph T. Meyerowitz.
Everyday Mapping of Traffic Conditions - An Urban Planning Tool Laboratory of Geodesy Aristotle University of Thessaloniki, Department of Civil Engineering.
Human Tracking System Using DFP in Wireless Environment 3 rd - Review Batch-09 Project Guide Project Members Mrs.G.Sharmila V.Karunya ( ) AP/CSE.
Advanced Algorithm Design and Analysis (Lecture 12) SW5 fall 2004 Simonas Šaltenis E1-215b
August 30, 2004STDBM 2004 at Toronto Extracting Mobility Statistics from Indexed Spatio-Temporal Datasets Yoshiharu Ishikawa Yuichi Tsukamoto Hiroyuki.
The Cutting Edge Training Your Art Museum Volunteers Need Group A – Curriculum Design Professionals  William LaFave  Maria Mancha  Frank Jaquez  Kendra.
An answer to your common XACML dilemmas Asela Pathberiya Senior Software Engineer.
Chapter 14 : Modeling Mobility Andreas Berl. 2 Motivation  Wireless network simulations often involve movements of entities  Examples  Users are roaming.
Minkyoon Kim, Sangjin Han1 Querying in Highly Mobile Distributed Environments T.Imielinski and B. R. Badrinath Minkyoon Kim Sangjin Han.
Location Privacy Protection for Location-based Services CS587x Lecture Department of Computer Science Iowa State University.
Efficient OLAP Operations in Spatial Data Warehouses Dimitris Papadias, Panos Kalnis, Jun Zhang and Yufei Tao Department of Computer Science Hong Kong.
Chapter. 3: Retrieval Evaluation 1/2/2016Dr. Almetwally Mostafa 1.
Managing Location Information for Billions of Gizmos on the Move – What’s in it for the Database Folks Ralf Hartmut Güting Fernuniversität Hagen, Germany.
Automating Work Order Processes for Advanced Metering Infrastructure (AMI) Devices with Collector for ArcGIS and Portal for ArcGIS Subrahmanyam Pendyala.
Continuous Monitoring of Spatial Queries in Wireless Broadcast Environments.
Getting Ready for the NOCTI test April 30, Study checklist #1 Analyze Programming Problems and Flowchart Solutions Study Checklist.
CAT: Correct Answers of Continuous Queries using Triggers
1st November, 2016 Transport Modelling – Developing a better understanding of Short Lived Events Marcel Pooke – Operational Modelling & Visualisation Manager.
COTS testing Tor Stålhane.
COTS testing Tor Stålhane.
Efficient Evaluation of k-NN Queries Using Spatial Mashups
Predicting Traffic Dmitriy Bespalov.
Dynamic Queries over Mobile Objects
Performance And Scalability In Oracle9i And SQL Server 2000
Spatial Databases: Spatio-Temporal Databases
Presentation transcript:

February 4, Location Based M-Services Soon there will be more on-line personal mobile devices than on-line stationary PCs. Location based mobile-services Moving users equipped with mobile phones, PDAs, etc., periodically disclose their positions to the service provider The service provider tracks the movement of the users and provides useful services: “If you want to get home faster today, do not turn into street X (where you will get into a traffic jam)” “On the right, you should see the Smithsonian Air and Space Museum – the museum you should definitely visit before leaving Washington D.C.”

February 4, LBS Architecture Service provider DBMS Locations of users Maps, other info Data structures Positioning Location info Service requests (queries) Services (location-specific, on-time, personalized information)

February 4, Reducing the Update-Load In LBS scenarios and in other pervasive computing scenarios (e.g., sensor nets) one of the problems is a high load of updates A million objects, each reporting its position once a minute: Too high communication loads A database may not be able to keep up (We want to handle as much as possible updates using a centralized database) If objects move completely randomly and we want to have very precise positions, not much can be done. In the real world: Objects move “orderly” We may be satisfied with reduced accuracy

February 4, Reducing the Update-Load Let the database have a much richer knowledge about the future predicted movement of objects and let the objects know what the database “assumes”: No matter how a road is twisted, if I move with a constant velocity on this road and the database knows the map of roads and my velocity, there is no need to keep reporting my position to the database Allow for lazy updates. Two step query processing: retrieve a larger candidate set, ask each of the objects to report its latest position, and check if it really satisfies the query The goal of the project would be to develop and evaluate these techniques assuming a specific type of data (e.g., positions of moving cars)

February 4, Indexing in Oracle Indexes are data structures that support fast answers to queries Commercial ORDBMSs support indices for static spatial data: “Find gas stations close to me” No support for the indexing of continuously moving objects: “Find customers close to my gas station”

February 4, Indexing in Oracle The goal of the project – to implement and compare a number of alternatives for how to index moving objects in Oracle: One could view moving objects represented by (x,y,v x,v y ) as four dimensional moving points and index them with the built-in spatial index One could try to use Oracle index-extensibility interface and implement a new index specifically for continuously moving points

February 4, Managing Traffic using DB The goal of this project would be to investigate a specific application area – traffic management using on-line vehicles: I want to maintain an overview (and possibly record a history of) the current traffic situation – an approximate number of vehicles on each segment of any road I need to maintain this aggregate information in the database, not enough just to have possitions of objects I want to ask “shortest-path” queries, that take into account traffic information

February 4, Managing Traffic using DB Two directions for the project: More theoretical (what kind of external data structures are needed, how external algorithms, e.g., graph algorithms, work) More practical – again, take Oracle and look how much we can squeeze out of it to implement the desired functionality

February 4, Realistic Data for Experiments Data from the tracking of a number of test cars in Aalborg. Moving object data generated with IBM's City Simulator

February 4, Contact Simonas Šaltenis and Michael Böhlen Mike is not at the university this week E1-215b and E1-215