スライド 1

Pre-Workshop
Discussion
2006-05-18 10:00 – 14:00
@102A1
Esaki Laboratory
Chapter
• Introduction (22 pages)
– Overview
– Evaluation
– Characteristics
• Accident (3 pages)
– Accidents already occurred
– Accidents we must assume
• Discussion (18 pages)
INTRODUCTION
• Historical System (weather.hongo)
– Overview
– Evaluation
– Characteristics
• New Approach (live-e.hongo)
– Concept (Sensor Abstraction)
– System Overview
– Characteristics
Live E! Project Overview
• A Sensor Network Infrastructure
• E stands for three meanings
– Earth
– Environment
– Electronics
• Application
– Public Service (such as for Natural Disaster)
– Business
– Education
INTRODUCTION
• Historical System (weather.hongo)
– Overview
– Evaluation
– Characteristics
• New Approach (live-e.hongo)
– Concept (Sensor Abstraction)
– System Overview
– Characteristics
Historical System
APP
Web Interface
APP
APP
Web Service(SOAP/XML)
weather.hongo.wide.ad.jp
Windows 2003 Server
MSSQL
WD
Upload with SOAP
WDDBLog
Vaisala Sensors
Vaisala Sensor(WXT510)
• Measure Item
–
–
–
–
–
–
–
Temperature
Humidity
Pressure (Barometer)
RainFall
WindDir
WindSpeed
(CO2)
WXT510
RS232C
Serial Interface
weather.hongo
Internet
iLon100
SOAP
Lonworks
WXT510s are connected to weather.hongo through Lonworks.
Behavior of Data Upload
Inside weather.hongo
TABLE WD
Current Data Table
neuron_id WNIID Time Temperature Humidity Pressure
RainFall
WindDir
WindSpeed CO2
Archive Data
TABLE WDDBLog
neuron_id Time Temperature Humidity Pressure
RainFall
WindDir
WindSpeed CO2
DATA MODEL
Update WD
Insert WDDBLog
Each sensor has
multiple sensor type
WeatherDataWrite
Web Service
Data
Vaisala Sensor
API (weather.hongo)
The Latest Sensor Data
Archived Sensor Data
XML
XML
Web Service
WeatherDataReadAll
WDReadLog
Select WD
Select WDDBLog
TABLE WD
Current Data Table
neuron_id WNIID Time Temperature Humidity Pressure
RainFall
WindSpeed CO2
Archive Data
TABLE WDDBLog
neuron_id Time Temperature Humidity Pressure
WindDir
RainFall
WindDir
WindSpeed CO2
Evaluation (weather.hongo)
• The Number of Sensor
– About 50.
• Upload Frequency
– Temperature, Humidity, Pressure, RainFall
• Every 5 minutes
– WindDir, WindSpeed
• Every 20 seconds
• WDDBLog Table Size
– Increases about 250,000 rows per day.
– Current Row Size is 39,863,725 (2006-05-16 10:12:00)
– A Query takes about 40 seconds.
Characteristics (weather.hongo)
• Designed by Echelon.
• What the Sensor is:
– Vaisala sensor (at least, sensor on Lonworks)
– Each sensor has multiple sensor type.
– Sensors can be identified by NeuronID.
• No sensor meta-information
– Sensor meta-information (sensor profile) must be
provided by other systems.
• Centralized
– No scalability, No robustness
INTRODUCTION
• Historical System (weather.hongo)
– Overview
– Evaluation
– Characteristics
• New Approach (live-e.hongo)
– Concept (Sensor Abstraction)
– System Overview
– Characteristics
New Approach (live-e.hongo)
• What the Sensor is: (Sensor Abstraction)
– Sensor ID of Live E!
• NeuronID is base on Lonworks system.
• We must make a new ID system.
• Globally-unique
– A single sensor type.
• Each sensor must have only one value.
• A Multiple sensor must be divided to single sensors.
– Profile
• Meta-information that describes sensor.
Sensor ID
• sensor_id
– Globally-unique ID
– Format (Syntax Rule)
• Domain Name + /SensorModel/Location/SensorType
– Example
•
•
•
•
•
live-e.org/WXT510/0300000431b2/Temperature
live-e.unl.im.dendai.ac.jp/WM918/kanda/12/roof/Temperature
live-e.unl.im.dendai.ac.jp/WM918/kanda/12/roof/Humidity
live-e.unl.im.dendai.ac.jp/WM918/kanda/12/roof/Pressure
mew.co.jp/FS-Va-01/aoyama_elementary_school/Temperature
• Semantics
– No meaning
– Just a String
Sensor Data
• Each sensor has a single value.
– The value can be determined by “sensor_id”
and sampled “time”.
value = F( sensor_id , time)
Ex. The result of GetCurrentData(sensor_id);
<d:Data xmlns:d=“http://live-e.org/Ver200603/Data”>
<value time=“2006-05-15T02:34:53.000+09:00”>23.5</value>
<d:Data>
(Major) Sensor Profile
•
•
•
•
•
•
•
sensor_id
sensor_model
sensor_type
latitude
longitude
location
address
(Ex. live-e.org/WXT5 ---/Temperature)
(Ex. WXT510)
(Ex. Temperature)
(Ex. 35.712194)
(Ex. 139.76775)
(Ex. 東大情報基盤センター)
(Ex.東京都文京区弥生2-11-16)
Sensor Profile Example
• GetProfile(“live-e.org/WXT510/ --- /Temperature”);
<p:Profile xmlns:p="http://live-e.org/Ver200603/Profile">
<sensor_id>live-e.org/WXT510/03000005c3a2/Temperature</sensor_id>
<sensor_vendor>vaisala</sensor_vendor>
<sensor_model>WXT510</sensor_model>
<sensor_type>Temperature</sensor_type>
<longitude>139.76775</longitude>
<latitude>35.712194</latitude>
<location>東大情報基盤センター</location>
<address>東京都文京区弥生2-11-16</address>
</p:Profile>
API (live-e.hongo)
• String GetCurrentDataAll();
• String GetCurrentData(String sensor_id);
• String GetCurrentDataByAreaRect(double,double,double,double);
• String GetCurrentDataByType(String sensor_type);
• String GetCurrentDataOf(String sensor_id_like);
• String GetDataByTimespan(String,Date,Date);
• String GetProfileAll();
• String GetProfile(String sensor_id);
• String GetProfileByAreaRect(double,double,double,double);
• String GetProfileByType(String sensor_type);
live-e.hongo
APP
APP
APP
Web Service(SOAP/XML)
Debian Etch
PostgreSQL8.1
Java+Axis
live-e.hongo.wide.ad.jp
weather.hongo
WXT510
WM918
FS-Va-01
Weather Station(WM918)
• Measure Item
– Temperature
– Humidity
– Pressure
– RainFall
– WindDir
– WindSpeed
live-e.hongo
WM918
Internet
PC
SOAP
RS232C
Field Server (FS-Va-01)
• Measure Item
–
–
–
–
–
–
–
–
–
–
Temperature
Humidity
Pressure
RainFall
WindDir
WindSpeed
Solar_Radiation
Soil_Moisture
Soil_Temperature
Photo
live-e.hongo
FS-Va-01
Internet
SOAP
DataCenter
Matsushita-Denko
Data Upload Protocol
• Protocol
– SOAP
• Data Format
– XML-like format
<Data>
<LiveE-ID>live-e.unl.im.dendai.ac.jp/WM918/kanda/12/roof/Temperature</LiveE-ID>
<Time>2006-05-12T04:34:42.0000+09:00</Time>
<Value>23.1</Value>
</Data>
・・・ <Data></Data> continues
Behavior of Data Upload
TABLE sensor_data_current
sensor_id time
TABLE sensor_data_log
data_index sensor_id time
value
Update
sensor_data_current
Insert
sensor_data_log
DB_INSERT
Data
Sensors
Web Service
value
Characteristics (live-e.hongo)
• Improved
– Sensor Abstraction
– Profile Management
• The same as weather.hongo
– Directly connected to the Database
• Upload Message Flow
• Query Processing
– Centralized
• All the sensors are managed in one database
• No scalability
Accident
• Accidents Already Occurred
– The Accident of New Measure Item
– The Accident of Software Update
• Accidents we must assume.
– Server Crush
– Rigid System
• Difficulty of introducing new architecture or new model.
– Database-oriented
– Sensors are deployed without managing
The Accident of New Measure Item
• There is another data archive system.
http://www.cnl.k.u-tokyo.ac.jp/~koba/live_e/index.php
– This system collects data by parsing HTML of
web interface of weather.hongo.
http://weather.hongo.wide.ad.jp/WDShow/WDShow.aspx
• One day, a new measure item
“DayRainFall” was added.
– Of course, the HTML structure was changed.
• The archive system went into out of order.
The Accident of Software Update
• Sensor data upload software had a bug.
– It had been already published.
– Isi removed the bug.
• Published again
• Announced
• One of us deployed the old version.
– The fact was found out by human check.
– live-e.hongo could not detect it.
WM918
live-e.hongo
Internet
PC
SOAP
RS232C
Discussion
Discussion Agenda
1. Evaluate the system in many aspects
– Scalability, Robustness, ... , etc.
2. Introduce related work.
3. Determine what we focus on ...
•
pub-sub? or range query? or any other?
4. Design prototype system
5. Determine what to do at the workshop
Evaluate Point
•
•
•
•
•
•
•
•
•
•
•
Scalability
Robustness
Flexibility
Reliability
Efficiency
Functionality
Availability
Feasibility
Heterogeneity Management
Automation
Simplicity
Scalability
• What is O(N)? N: The Number of Node.
• Resource Capacity VS O(N).
– R>>O(N) at N=1,000,000 → Scale
– R<O(N) at N=1,000,000 → Does Not Scale
• Current System (live-e.hongo)
– Does not scale!!
• What do we need to introduce to obtain
scalability?
Robustness (Tolerance)
• What would happen if ... ?
– A server crushed.
– Disconnected.
• Current System
– It must be a disaster.
•
•
•
•
Lose the data archived
Out of Service
Cannot collect sensor data
Take time to comeback
• What do we have to do to obtain tolerance?
Flexibility
• Is it easy to extend ... ?
– easy to add some functions ?
– easy to add resources ?
(such as disk space or CPU)
• Current System
– Rigid.
– Each parts are tightly dependent.
– We need lots of energy to remodel.
• How do we design a flexible system?
Reliability
• Is the data correct?
– Can we trust the value of sensors?
– How deep can we detect irregular behavior?
– Who has the responsibility of the data?
– Certification
• Current System
– Trust all the sensor even if one of them said -324℃
• What do we need to improve reliability?
Efficiency
• Low cost?
– Time, Money, Power, Space ...
– It is said... The cost is:
• big central > small distributed
• Current System
– Unknown
• It is important to think of efficiency when
we design system.
Functionality
• Complex Query OK?
– Range query
• Current system
– Good
• How do we obtain functionality within the
system?
Availability
• Is Live E! system opened?
• Example of open system
– Internet
– DHT
• Current System
– Not opend
– Only the system manager can control the system.
• How do we provide availability?
Feasibility
• Can we execute the plan?
– Human Resource
– Money
– Law
• We have to consider whether we can do it
or not.
Heterogeneity Management
• How do we manage sensors uniformly?
– Abstraction?
– Namespace Management?
Automation
• What do we need to design system to
work automatically?
– When software updated.
– When resource added.
Simplicity
• Simpler, More User
• Few would like to learn complex access
methods.
RELATED WORK
• Content-Based Network
– Publish-Subscribe Service
• DHT (Distributed Hash Table)
– i3 (publish-subscribe on DHT)
– PHT (range query on DHT)
• Caching
• Live Update
• Sensor Abstraction
What we focus on ...
•
•
•
•
•
Publish - Subscribe Model
Range Query
Data Mining
The Abstraction of Sensor
Live Update
Prototype System
• Depends on what we focus on ...
• Talk about these:
– Architecture
– Interface and Protocol
– Evaluation
– Who
At the Workshop
• Evaluate the system.
– What do you want to do?
– I want to do something aggressive.
Ex. Increase virtual sensors until the system fails.

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