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Development of a Sensor Database System for Communication Robots. Hideyuki KAWASHIMA Graduate School of Keio University Yokohama, JAPAN. Background: Human-Robot Communication. Sensors Video Microphone Touch sensor Ultrasonic sensor. Required properties.
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Development of a Sensor Database System for Communication Robots Hideyuki KAWASHIMA Graduate School of Keio University Yokohama, JAPAN
Background:Human-Robot Communication • Sensors • Video • Microphone • Touch sensor • Ultrasonic sensor
Required properties • Monitoring sensor data during experiments • Persisting precious sensor data immediately • Retrieving similar sensor sequences
Problem formulation • Continual query • Freshness of data • Similar sequence retrieval
Problem1: Continual query Sensor Monitoring Client DB Data 1 Data 2 Data 3 Backend DBMS IPC waste & period lag
Problem2:Freshness of Data Sensor Process Database backend Buffer Pool Stale databecause of Tardy disk access Log file
(Di-Qi) 2 Σ √ 2/5 Wk Σ MIN{ } K 5 4 16 9 4 1 3 9 4 1 0 2 4 1 0 1 1 2 3 4 1 0 1 4 Problem3:Similar Sequence Retrieval • Metrics • Euclid: • Dynamic time warping: = 2 = Wk = A distance on a path 5 4 3 4 3 2 2 1
My approach: Extending RDBMS for problems • Continual query • Freshness of data • Similar sequence retrieval
Continual query Sensor Monitoring Client Register CQ DB Transfer Backend Data 1 Data 2 Monitoring Backend Data 3 DBMS Efficient IPC & Exactly periodic monitoring
Freshness of data Sensor Process Database backend Buffer Pool Network Remote log server & Check pointer
Similar sequence retrieval • Select sonar from robovie where simseq external [1,2,3] with dtw < 10 Sliding window: 1 2 3 id Experiment_date sonar 1 01/05/2004 2 02/05/2004
Design of KRAFT Trans. Mgr Storage Mgr Mem. Mgr Index Mgr Mem. Mgr Lock Mgr Remote Log Mgr Parser Executor Recovery Mgr Conn. Mgr Local Log Mgr TCP TCP Over 17000 lines by C Client
Future directions • Enhancing analytical methods for sensor data • Scalability for continual monitors • Accelerating query processing • Index for similarity retrieval • Parallel execution • Device conscious
Summary • Motivation • Management of data for human-robot interactions • Problems • Continual query • Freshness of data • Similar sequence retrieval • My approach • Extending RDBMS for problems • Future directions