performance analysis of a user-centric crowd-sensing water ... · performance analysis of a...
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Nikolaos Rapousis and Maria Papadopouli
UNIVERSITY OF CRETE Department of Computer Science
Department of Computer Science, University of Crete Institute of Computer Science, Foundation for Research & Technology – Hellas (FORTH)
http://www.ics.forth.gr/mobile
Speaker: Nancy Panousopoulou
This research has been funded by a GSRT Research Excellence grant (2012-2015), a Google Faculty Award (2013-2014), and EU Hydrobionets
13-Apr-2015 CySWater 1
Performance Analysis of a User-centric Crowd-sensing Water Quality Assessment System
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Resources WHH-WASH Sector Report, FAO, WHO, UN
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Roadmap
• Introduction & Motivation
• Related work
• QoWater system
• Proof-of-concept & pilot testbed
• Preliminary field study & evaluation results
• Conclusions and future work
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Contamination events
• Pressure loss or change may result in backflow incidents during which contaminated soil water enters the water distribution network (WDN) through pipe breaks or leaking joints
• Corrosion of iron, copper, and lead parts of the WDN (e.g., due to free chlorine for disinfection)
• Bioterrorism
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Motivation • Efficient monitoring & management of the infrastructure, including the last-mile access
network
• User in the loop: user engagement
• Increased customer awareness about the water quality & querying mechanisms
• Fast & efficient warning/alerting in the case of contamination
• More accurate models for assessing the quality of the water
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Roadmap
• Introduction & Motivation
• Related work
• QoWater
• Proof-of-concept
• Evaluation
• Conclusions and future work
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Related activities in water contamination
1. Mobile apps for querying specific sensors & providing feedback (e.g., [Jonoski13], Delhi Jar board, 311)
2. Sensor placement for supporting warming systems, e.g., [TriopuNet12, Pelerman15, Krause08]
3. Detection algorithms for drinking water contamination, e.g., [Whelston’07, Dietrich’14, Mix12]
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Roadmap
• Introduction
• Related work
• QoWater system
• Proof-of-concept
• Evaluation
• Conclusions future work
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Health Organization sensors
Citizens/Customers with QoWater client
Water Distribution Network
QoWater client
QoWater server
Regulators, administrators, scientists
sensors
sensors
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QoWater system: client-to-server architecture
QoWater clients on mobile devices
• Collect customer/scientist sentiments & store them locally
• Upload data to the QoWater server
• Query the QoWater server to acquire quality related info for various regions
QoWater server
• Collects client and sensor data in spatio-temporal geo-DB
• Responds to queries sent by users, providers & regulators
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Sensor measurements pH, temperature, conductivity oxidation-reduction potential & Ion Chlorine
Main screen
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Query based on clients score or sensor measurements
Results for query area, based on clients option eg, customer score
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Registration form for the Customer role
Registration form for the Scientist role
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Color: red/brown, green/blue, white, black Taste: bitter, salty, sweet Odor: sewer, chlorine, gasoline, chemical Appearance: floating particles, sand, milky, rusty, stain, animal, plant Pressure: no water, low, high Photo: required if Appearance problem exist
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Taste: bitter, salty, sweet Odor: sewer, chlorine, gasoline, chemical Appearance: floating particles, sand, milky, rusty, stain, animal, plant Pressure: no water, low, high
Chemical: turbidity, Br, Cl, Na, K, Mg2, biochemical oxygen demand, acidity, disssolved oxygen, etc Biological: ephemeroptera, plecoptera, excherichia coli, coliform bacteria, etc
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QoWater Architecture QoWater server
Secure sensor readings upload
Certificate Manager
Memcached service
Certificate Authority
Data receiver
Query handler
Access control
geoDB
Event detector
Data validator
Analyzer
HTTP service
PHP application
Upload data
QoWater sensor node
Broadcast sensor readings
Monitor
Temperature
Conductivity
ORP
PH
Chlorine ions
Back-end interface
WiFi interface
QoWater client
Android device
Po
siti
on
Qu
erie
s
Save
dat
a
Data Recorder
Cu
sto
mer
Fo
rm
Scie
nti
st
Form
Qu
eryi
ng
GUI
Sensor reading
GPS
Camera
Feedback
CSV
Measurement location
Back-end interface
Save sensor readings
SQLite
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QoWater server
Secure sensor readings upload
Certificate Manager
Memcached service
Certificate Authority
Data receiver
Query handler
Access control
geoDB
Event detector
Data validator
Analyzer
HTTP service
PHP application
Upload data
QoWater sensor node
Broadcast sensor readings
Monitor
Temperature
Conductivity
ORP
PH
Chlorine ions
Back-end interface
WiFi interface
QoWater client
Android device
Po
siti
on
Qu
erie
s
Save
dat
a
Data Recorder
Cu
sto
mer
Fo
rm
Scie
nti
st
Form
Qu
eryi
ng
GUI
Sensor reading
GPS
Camera
Feedback
CSV
Measurement location
Back-end interface
Save sensor readings
SQLite
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Rely on the end-to-end security that protects the integrity & confidentiality by leveraging standard technologies (eg public-private key pairs, TLS)
Use Hadoop Distributed FS & Hbase for higher aggregate I/O throughput
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Preliminary field study
Three sources of drinking water: tap, purified, bottled
Objective measurements by sensor node • Duration of sampling: 36 minutes • One data point every 10 seconds • Collection of 215 data points (omit the first 50 data points)
Subjective measurements (QoE score) by 44 subjects • Three cups containing tap, purified & bottled water with no indication of the source of the water • Each subject inspects, smells, tastes the water from each cup and provides its score immediately
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QoWater Testbed Sensor • with a micro-controller that operates at 14MHz frequency • 8 KB RAM memory, 2 GB SD card • IEEE802.11b/g WiFi
Server • VM with 2 cores at 2.4 GHz • 4 GB RAM, 27 GB storage • Ubuntu 14.04 OS
Client • Android 2.1 OS • 512 MB RAM • 3.7 inches (480 x 800)
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Emulated QoWater clients • VM with 12 cores at 2.4 GHz • 32 GB RAM, 150 GB storage • Windows7
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Scenario Step QoWater
Uploading QoWater Querying
QoWater Client-Sensor
U-map Querying
U-map Uploading
Skype Call
YouTube Streaming
1 Unlock phone Unlock phone Unlock phone Unlock phone Unlock phone Call a contact Unlock phone
2 Launch QoWater Launch QoWater Launch QoWater
Launch u-map
Launch u-map
Call duration 20 sec
Launch YouTube
3 Tap Sentiment Tap Search Tap Sensor Tap Upload data
Tap Select Operator
N/A Display 78 sec video
4 Fill complaint form
Retrieve user location
Display 35 sec sensor measurements
Upload 4.8 MB data
Tap Polygon N/A Return to Home Screen
5 Fill 5 star QoE Tap Query Area Return to Home Screen
N/A Tap Submit N/A N/A
6 Upload 1.5 MB data
Display response N/A N/A Display response
N/A N/A
7 Return to Home Screen
Return to Home Screen
N/A N/A Return to Home Screen
N/A N/A
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Evaluating: Response Delay Testbed
QoWater client (Android)
QoWater server
T1
T2
T5
T6
T3
T4
Query
Display
Response generation
time
AP
internet
Android Delay Network Delay
Server Delay
Network Delay Android Delay
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QoW client (Android)
QoW server
T2
T6
T4
Query
Display
Response generation
time
AP Internet
T1
T5
T3
Evaluating: Response Delay Testbed (2)
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Response Delay
Scenario Android/Waspmote Server Network Total (ms)
QoWater: Uploading 393 (52) 69 (5) 249 (47) 711
QoWater: Querying 102 (19) 1451 (83) 262 (66) 1815
QoWater: Sensor 4000 (233) 32 (1) 4000 (500) 8023
U-map: Uploading 49 (N/A) 159 (N/A) 379 (N/A) 587
U-map: Querying 43 (N/A) 135 (N/A) 8 (N/A) 186
• Each scenario was executed 20 times • QoWater sensor uploading is the most time consuming (background does not effect response) • Note that u-map users different dataset size and response processing
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Power Consumption
Start AppScope
End AppScope
Launch application
AppScope Inter Process Communication
Execute scenario
Exit application
Start AppScope
End AppScope
Collect measurements
Create report
• AppScope for the energy measurements • QoWater client is an HTC Nexus One smartphone • Compare the QoWater with the u-map & popular apps (e.g., Skype, YouTube)
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Power Consumption (con’td)
Scenario CPU Display GPS WiFi Total (mW)
QoWater: Uploading 68 (14) 712 (10) 17 (1) 23 (7) 803 820
QoWater: Querying 56 (3) 548 (15) 17 (1) 8 (3) 612 629
QoWater: Sensor 4 (1) 767 (10) 0 1 (0) 772
U-map: Uploading 35 (23) 567 (1) 0 88 (14) 690
U-map: Querying 33 (3) 563 (15) 0 6 (4) 770
YouTube: Video 23 (3) 786 (5) 0 6 (4) 815
Skype: Call 111 (14) 639 (15) 0 57 (20) 807
Suspended: 3 (1) 0 0 6 (3) 9
• 100 repetitions of each scenario • The 3G has been omitted • Display is the most energy demanding in all scenarios
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Scalability
Response Delay
Served vs. Time-out
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V-Trickle vs Periodic
V-Trickle extends the battery lifetime approximately 4 times
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Conclusions
• The QoWater is a monitoring & querying mechanism that can engage citizens, improve the transparency of the monitoring process and provide alerts in case of contamination events
• Relatively low response delay and power consumption • Most demanding scenario consumes less than a 20 sec Skype call • Current server cannot adequately support large-scale regions – possible solutions through
cloud computing • Preliminary earlier field study indicates that users can distinguish different sources of water
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Future work
• Analysis of the user sensitivity regarding the water quality • Prediction models of contamination events based on extensive field studies • Analysis of the impact of incentives to enhance the participation of citizens on systems
adoption
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Questions