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Intelligent Environments1 Computer Science and Engineering University of Texas at Arlington.

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Presentation on theme: "Intelligent Environments1 Computer Science and Engineering University of Texas at Arlington."— Presentation transcript:

1 Intelligent Environments1 Computer Science and Engineering University of Texas at Arlington

2 Intelligent Environments2 Databases for Intelligent Environments Requirements Technologies Evaluation Architecture

3 Intelligent Environments3 Database Requirements

4 Intelligent Environments4 Database Requirements

5 Intelligent Environments5 Data Storage Requirements Sensor data Temperature 8 Kbps) Humidity 8 Kbps) Gas 8 Kbps) Light 8 Kbps) Motion 8 Kbps) Pressure 8 Kbps) Microphone 500 Kbps) Camera 10 Mbps)

6 Intelligent Environments6 Data Storage Requirements User data Multimedia Phone messages/conversations (500 Kbps – 10 Mbps) Music (500 Kbps) TV/Radio broadcasts (500 Kbps – 10 Mbps) Home movies (10 Mbps) Images Computer Programs Data files Operating systems

7 Intelligent Environments7 Data Storage Requirements Issues Query frequency and type Sampling/recording rates 205 sensors (158,900 Kbps) Multimedia recordings Simultaneous playback Analysis, prediction, decision-making queries Transaction granularity Historical data, decay Security and privacy Centralized vs. distributed

8 Intelligent Environments8 Database Technologies

9 Intelligent Environments9 Database Technologies Commercial DB2 Empress Informix Oracle MS Access MS SQL Sybase Free Berkeley DB PostgreSQL MySQL

10 Intelligent Environments10 DB2 Vendor: IBM Availability: Commercial ($300) Features Comprehensive

11 Intelligent Environments11 Empress Vendor: Empress Availability: Commercial ($ call) Features Designed for embedded, real-time applications

12 Intelligent Environments12 Informix Vendor: IBM (acquired from Informix) Availability: Commercial ($ call) Features Parallel databases Object relational

13 Intelligent Environments13 Oracle Vendor: Oracle Availability: Commercial ($300) Features Comprehensive

14 Intelligent Environments14 MS Access Vendor: Microsoft Availability: Commerical ($329 with Office Professional) General purpose Designed for individual users

15 Intelligent Environments15 MS SQL Vendor: Microsoft Availability: Commercial ($5,000) Features General purpose Designed for enterprise users

16 Intelligent Environments16 Sybase Vendor: Sybase Availability: Commercial ($1,000) Features General purpose

17 Intelligent Environments17 Berkeley DB Vendor: UC Berkeley Availability: Free Features Designed for embedded systems applications

18 Intelligent Environments18 MySQL Vendor: MySQL Availability: Free Features General purpose

19 Intelligent Environments19 PostgreSQL Vendor: Open source effort Availability: Free Features General purpose

20 Intelligent Environments20 Intelligent Environments Database Evaluation

21 Intelligent Environments21 Database Benchmarking Transaction Processing Performance Council (TPC) Rigorously-defined benchmarks Independent regulatory body TPC benchmarks TPC-C, TPC-H, TPC-R, TPC-W

22 Intelligent Environments22 TPC-C Benchmark Simulates complete computing environment Multiple users executing transactions against a database Order-entry scenario Entering and delivering orders Recording payments Checking order status Inventory monitoring Metrics Transactions per minute (tpmC) Price per transaction ($/tpmC)

23 Intelligent Environments23 TPC-H Benchmark Decision support benchmark Examine large volumes of data Answers to critical business questions Complex queries Data modifications Metrics Composite Query-per-Hour Performance Metric Size of database Single-stream query processing power Concurrent query throughput

24 Intelligent Environments24 TPC-R Benchmark Decision support benchmark Similar to TPC-H Advanced knowledge of queries Allows optimization Metrics Composite Query-per-Hour Performance Metric

25 Intelligent Environments25 TPC-W Benchmark Web transactions benchmark E-commerce scenario Multiple browser sessions Dynamic page generation with database access and update Simultaneous transaction execution Heterogeneous database tables (sizes, attributes, relationships) Metrics Web interactions processed per second (WIPS, $/WIPS)

26 Intelligent Environments26 TPC Results Best TPC-C 709,220 tpmC (MS SQL) TPC-H 100GB: 5578 QphH (Oracle) 300GB: 5976 QphH (Oracle) 1000GB: 25,805 QphH (Oracle) 3000GB: 79,528 QphH (Teradata) 10,000GB: 81,501 QphH (Teradata)

27 Intelligent Environments27 TPC Results Best TPC-R 100GB: 4442 QphR (Oracle) TPC-W 10,000 items: 21,139 WIPS (MS SQL) 100,000 items: 10,439 WIPS (MS SQL) More results at

28 Intelligent Environments28 Other Benchmarks Wisconsin Relational queries AS3AP ANSI SQL Scalable and Portable benchmark Mix of transactions, relational queries, and utility functions Open Source Database Benchmark (OSDB) Based on AS3AP

29 Intelligent Environments29 Analysis High-end database transaction processing power 600,000 tpm = 10,000 tps Sensor recording transactions 15 temp/hum/gas/light/motion, 100 pres 175 tps 15 cameras (30 fps) / 15 microphones (64 Kbps) 465 tps, or 120,450 tps (one-byte mic transactions) Multimedia recording transactions Prediction and decision-making queries System information

30 Intelligent Environments30 Intelligent Environments Database Architecture

31 Intelligent Environments31 Database Architecture Issues (again) Query frequency and type Sensors Multimedia recording and playback Analysis, prediction, decision-making queries User data System information Transaction granularity Historical data, decay Security and privacy Centralized vs. distributed

32 Intelligent Environments32 Sensor Database Systems COUGAR project Query processing over ad-hoc sensor networks Small database component (QueryProxy) at each sensor Sensor clusters provide local aggregations (e.g., min, max, mean) Assumes centralized index of all data sources

33 Intelligent Environments33 Siemens Netabase “The network is the database.” Navas and Wynblatt, ACM SIGMOD 2001 Sensor networks Large number of data sources (105) Volatile data and data organization “Thin” data servers on scaled-down hardware Netabase approach Query decomposition Characteristic routing (ala IP routing) Local joins Query evaluation

34 Intelligent Environments34 Siemens Netabase

35 Intelligent Environments35 SmartHome Database Architecture

36 Intelligent Environments36 SmartHome Database Architecture Centralized vs. distributed? Answer: Both Central storage of high demand, persistent data Distributed storage of low demand, dynamic data Distributed queries Push processing toward sensors Adaptive, hierarchical organization End-effector autonomy (“smart sensor”)

37 Intelligent Environments37 UTA MavHome Smart Home


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