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Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Talk at Skolkovo Institute of Science and Technology, Moscow, Russia, October 2, 2014.
Indoor Data Management: Status and Challenges
Demetris Zeinalipour
Data Management Systems Laboratory
Department of Computer Science
University of Cyprus
http://dmsl.cs.ucy.ac.cy/
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/142
Motivation• People spend 80-90% of their time indoors –
USA Environmental Protection Agency 2011.• >85% of data and 70% of voice traffic
originates from within buildings – Nokia 2012.
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/143
Computing Shift• October 2011: The Economist. "Beyond the PC"
• February 2012: Canalys validated Economist's forecast, initiating the Post-PC era.
• April 2013: IDC reports another important development– Smartphone sales exceed the sale of Feature phones for the
first time in history due to increased sales in developing regions.
– 51.6% (216M) Smartphones vs.
48.4% (186M) Feature Phones
Sa
les (M
illion
s)
Year
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/144
Computing Shift
Source: http://goo.gl/vYJZCJ
• Power-efficient Von-Neumann Architecture Artifacts
• Latest Smartphone SOC (Qualcomm Snapdragon 810) features 4 x A57 (faster) cores + 4 A53 (eco) cores with 64 bit support and 20nm device fabrication
• Indicative benchmark:– Intel Xeon X5650 (6-cores,
2.67GHz): 13,703
– Snapdragon 801 (4-cores, 2.45GHz): 2,924
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/145
Networking Shift Wireless Data Transfer Rates
Plot Courtesy of H. Kim, N. Agrawal, and C. Ungureanu, "Revisiting Storage for Smartphones", Best Paper Award at the 10th USENIX Conference on File and Storage Technologies (FAST'12), San Jose, CA, February 2012.
4G ITU peak rates:•100 Mbps (high mobility, such as trains and cars) •1Gbps (low mobility, such as pedestrians and stationary users)
Storage Interfaces on Servers:iSCSI(1Gbps or 10Gbps), SAS (6Gbps), FC(8Gbps)
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/146
• A smartphone crowd is constantly moving and sensing providing large amounts of opportunistic data enabling new applications
Human Shift
“Crowdsourcing with Smartphones”, Georgios Chatzimiloudis, Andreas Konstantinidis, Christos Laoudias, Demetrios Zeinalipour-Yazti, IEEE Internet Computing, Special Issue: Sep/Oct 2012 - Crowdsourcing, May 2012. IEEE Press, Volume 16, pp. 36-44, 2012.
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/147
The Indoor Frontier• Indoor Applications using Smartphones:
– In-building Navigation: Museums, Airports, Malls– Asset Tracking and Inventory Management– Augmented Reality– Smart Houses and Elderly support
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/148
Indoor Data Management• Indoor Data Management, deals with all aspects of
handling data as a valuable resource: acquisition, modeling, processing, query processing, privacy, energy, etc.
• In this overview talk, I will attempt to cover the current state but also identify future challenges.
• The presentation is carried out through the lens of an experimental Indoor Information System we developed at the University of Cyprus, coined Anyplace.
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/149
Viewer, Widget
Navigator
Modeling
Anyplace Indoor Information Service
Location
Processing / Indexing
Privacy, Search
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1410
Presentation Outline• Indoor Data Management
– Introduction– Location– Privacy– Modeling– Testbeds– Latest: Big-data, Device Diversity,
Prefetching Radiomaps
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1411
Location• Location (position): identifies a point or an area on
the Earth's surface.• Global Navigation Satellite Systems (GNSS) have played
an important role in Outdoor (Spatial) Data Management:• Current: Global Positioning System (US), GLONASS (Russian)• Upcoming: Galileo (European), Indian Regional Navigation Satellite
System (IRNASS), BeiDou-2 (Chinese) – Many civilian uses with advent of GIS technologies since ‘70 (ESRI)
Location-based ServicesPrecision AgricultureGeographic MappingNavigation
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1412
Location (Outdoor)• GNSS Drawbacks for Indoor Location:
– Low availability indoors due to the blockage or attenuation of the satellite signals.
– High start-up time.– Power Demanding (continuously receive signals).
Zeinalipour et. Al IEEE Internet Computing 2012
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1413
Location (Outdoor)• Cell ID:
– Cell ID is the Unique Identifier of Cellular Towers.
• Cell ID Databases– Skyhook Wireless (2003), MA, USA (Apple,
Samsung): 30 million+ cell towers, 1 Billion Wi-Fi APs, 1 billion+ geolocated IPs, 7 billion+ monthly location requests and 2.5 million geofencable POIs.
– Google Geolocation “Big” Database (similar)
Disadvantages:• Low accuracy: 30-50m
(indoor) to 1-30km (outdoor).• Serving cell is not always the
nearest.
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1414
Location (Indoor)• Inertial Measurement Units (IMU)
– 3D acceleration, 3D gyroscope, digital compass using dead reckoning (calculate next position based on prior).
• Disadvantages– Suffers from drift (difference between where the
system thinks it is located, and the actual location)
• Advantages– Sensors are available on smartphones.– Newer smartphones (iphone 5s) have motion co-
processors always-on reading sensors and even providing activitity classifiers (driving, walking, running, or sleeping, etc.)
wikipedia
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1415
Location (Technologies)
Rainer Mautz, ETH Zurich, 2011
: Spatial extension where system performance must be guaranteed
|
In
do
or
||
Ou
tdo
or
|
Hybrid
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1416
• References– [Airplace] "The Airplace Indoor Positioning
Platform for Android Smartphones", C. Laoudias et. al., Best Demo Award at IEEE MDM'12. (Open Source!)
– [HybridCywee] "Indoor Geolocation on Multi-Sensor Smartphones", C.-L. Li, C. Laoudias, G. Larkou, Y.-K. Tsai, D. Zeinalipour-Yazti and C. G. Panayiotou, in ACM Mobisys'13. Video at: http://youtu.be/DyvQLSuI00I
– [UcyCywee] IPSN’14 Indoor Localization Competition (Microsoft Research), Berlin, Germany, April 13-14, 2014. 2nd Position with 1.96m! http://youtu.be/gQBSRw6qGn4
– [Anyplace] Crowdsourced Indoor Localization and Navigation with Anyplace, In ACM/IEEE IPSN’14
– 1st Position at EVARILOS Open Challenge, European Union (TU Berlin, Germany).
Cywee / Airplace
WiFi Fingerprinting in Anyplace
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1417
WiFi Fingerprinting• Received Signal Strength Indicator (RSSI)
– Power measurement present in a received radio signal measured in [ dBm, Decibel-milliwatts, x = 10.log10(P / 1mW) ]
• 80 dBm = 100 kW Transmission power of FM radio (50 km)• 0 dBm = 1 mW• -80dBm = 10 pW | Max RSSI (-30dBm) to Min RSSI: (−90 dBm)• -110dBm = 0.01 pW | WiFi AP is visible but out of data range.
• Advantages– Readily provided by smartphone APIs .
– Low power 125mW (RSSI) vs. 400 mW (transmit)
• Disadvantages– Complex propagation conditions (multipath, shadowing)
due to wall, ceilings.
– RSS fluctuates over time at a given location (especially in open spaces).
– Unpredictable factors (people moving, doors, humidity)
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1418
WiFi Fingerprinting• Mapping Area with WiFi Fingerprints
– n APs deployed in the area
– Fingerprints ri = [ ri1, ri2, …, rin]
– Averaging )(1
1 mrrM
m iMi
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1419
WiFi Fingerprinting• Mapping Area with WiFi Fingerprints
– Repeat process for rest points in building. (IEEE MDM’12)– Use 4 direction mapping (NSWE) to overcome body
blocking or reflecting the wireless signals. – Collect measurements while walking in straight lines
(IPIN’14)
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1420
WiFi Positioning• Positioning with WiFi Fingerprint
– Collect Fingerprint s = [ s1, s2, …, sn]
– Compute distance || ri - s || and position user at:
• Nearest Neighbor (NN)
• K Nearest Neighbors (wi = 1 / K)
• Weighted K Nearest Neighbors (wi = 1 / || ri - s || )
s = [ -70, -51]
RadioMap
r1 = [ -71, -82, (x1,y1)]r2 = [ -65, -80, (x2,y2)]…rN = [ -73, -44, (xN,yN)]
NN, KNN, WKNN
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1421
WiFi Positioning Demo
"The Airplace Indoor Positioning Platform for Android Smartphones", C. Laoudias, G. Constantinou, M. Constantinides, S. Nicolaou, D. Zeinalipour-Yazti, C. G. Panayiotou, Best Demo Award at IEEE MDM'12. (Open Source!)
Video
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1422
Hybrid IMU/WiFi Positioning• We engaged in an Industrial NRE contract with Cywee Taiwan Ltd, a
hardware/software motion processing company (Mobisys’13)• The result was a Hybrid IMU/WiFi Positioning system with the following additional
features:– Location Fusion: WiFi / IMU (3-axis accelerometer, gyroscope, and digital compass) using a
particle filter.– MapMatching: to handle inaccurate IMU location estimates (e.g., void passing through walls).– Magnetic Mapping: detect and handle magnetic abnormalities due to electrical appliances
and refining the orientation.
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1423
Hybrid WiFi/IMU Positioning Demo
“Indoor Geolocation on Multi-Sensor Smartphones", C.-L. Li, C. Laoudias, G. Larkou, Y.-K. Tsai, D. Zeinalipour-Yazti and C. G. Panayiotou, in ACM Mobisys'13. Video at: http://youtu.be/DyvQLSuI00I
Video
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1424
Presentation Outline• Indoor Data Management
– Introduction– Location– Privacy– Modeling– Testbeds– Latest: Big-data, Device Diversity,
Prefetching Radiomaps
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1425
Location Privacy• An Indoor Positioning Service can continuously
“know” (surveil, track or monitor) the location of a user while serving them.
• Location tracking is unethical and can even be illegal if it is carried out without the explicit user consent.
• Imminent privacy threat, with greater impact that other location tracking concerns, as it can occur at a very fine granularity. It reveals:
– The stores / products of interest in a mall.– The book shelves of interest in a library– Artifacts observed in a museum, etc.
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1426
Location Privacy• Users don’t know where IPS operate their data and
whether these conform or not to latest legislative efforts and reforms:
– EU Data Protection Directive.
– US White House Counsumer Privacy Bill of Rights
– US-EU Safe Harbor guidelines
– US Do-Not-Trck Online Act
• IPS might become attractive targets for hackers, aiming to steal location data and carry out illegal acts (e.g., break into houses).
• IPS should be considered as fundamentally untrusted entities, so we aim to devise techniques that are exploit IPS utility with controllable privacy to the user.
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1427
Assumptions• No Low-level attacks:
– No spoofing or buffer overflow attacks by IPS– Attacks can be thwarted by network operators, Secure
communication channels, firewalls, etc.
• No modified responses– External entity could certify that IPS returns consistent responses.
• No Access to User Identifiers– Mobile Equipment Identifier (MEID), Network
Identifiers (MAC, IP), Cookies and Tracking Codes.– Can be prevented, changed or obfuscated (e.g., IP
anonymization networks I2P)
• Our aim is to protect only against an untrusted IPS– NSA is reveiled to track cellphone locations worldwide (5B records /
day) for Co-traveler and other projects.
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1428
Location Privacy
RadioMap Service
...
I can see these Reference Points,
where am I?
(x,y)!
User u- Privacy-Preserving Indoor Localization on Smartphones, Andreas Konstantinidis, Paschalis Mpeis, Demetrios Zeinalipour-Yazti and Yannis Theodoridis, in IEEE TKDE’14 (second round).- Towards planet-scale localization on smartphones with a partial radiomap", A. Konstantinidis, G. Chatzimilioudis, C. Laoudias, S. Nicolaou and D. Zeinalipour-Yazti. In ACM HotPlanet'12, in conjunction with ACM MobiSys '12, ACM, Pages: 9--14, 2012.
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1429
Temporal Vector Map (TVM)
RadioMap (server-side)
WiFi
WiFi
WiFi
...
Bloom Filter (u's APs)
K=3 Positions
User u
Set Membership Queries• Contains false positives • Doesn’t contain false negatives
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1430
TVM – Bloom FiltersBloom filters – basic idea:
- allocate a vector of b bits, initially all set to 0- use h independent hash functions to hash every
Access Point seen by a user to the vector.
The filters any bloom(row) that overlaps with the query bloom filter (i.e., bitwise &)
0 1 0 0 1 0 0 1 0 0
AP2AP13AP2 AP13
b
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1431
TVM – Bloom Filters• The most significant feature of Bloom filters is that there
is a clear tradeoff between b and the probability of a false positive.– Small b: Too many false positives– Large b: “No” false positives
• Given h optimal hash functions, b bits for the Bloom filter we can estimate the amount of false positives produced by the Bloom filter:
– False Positive Ratio:
– Size of vector:
h-h/b )e-(1fpr
)fpr-ln(1
h b
h
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1432
TVM ContinuousCamouflage trajectories
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1434
Presentation Outline• Indoor Data Management
– Introduction– Location– Privacy– Modeling– Testbeds– Latest: Big-data, Device Diversity,
Prefetching Radiomaps.
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1435
Modeling• Indoor spaces exhibit complex topologies. They are
composed of entities that are unique to indoor settings: – e.g., rooms and hallways that are connected by doors.– Conventional Euclidean distances are inapplicable in indoor space,
e.g., NN of p1 is p2 not p3.
Jensen et. al. 2010
Symbolic Model used in Anyplace
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1436
Modeling• Geometric Model: uses points in N-dimensional
space, allowing the calculation of Lp-norm distances.• Symbolic Model: uses reference points (e.g., rooms)
to establish a structure for distance computation.• We use a graph-based model G(V,E), V={rooms}
E={doors,corridors,stairs,elevators} - Becker 2005.• This allows direct usage of graph algorithms
(shortest path, connectivity, traversals, etc.)• To provide spatial range queries, we additionally need
to a complementary geometric extend to V.
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1437
Anyplace Viewer: http://anyplace.cs.ucy.ac.cy/
Modeling
Video
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1438
Presentation Outline• Indoor Data Management
– Introduction– Location– Privacy– Modeling– Testbeds– Latest: Big-data, Device Diversity,
Prefetching Radiomaps.
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1439
Smartphone Testbeds• Experimenting with real smartphones
encapsulates logistical challenges.– Measure power consumption with profiler or
localization accuracy at various locations in a building without moving around.
– Manage experimental data for trace-driven experimentation (repeatability or mockup experiments).
– Manage a smartphone cluster on 50 buses moving in a city and collecting network state (MAC, Cell-ID, etc.)
– Study Linear Correlation of RSSI across different 802.11 networking stacks in a controlled environment.

"Managing smartphone testbeds with smartLab”, G. Larkou, C. Costa, P. Andreou, A. Konstantinides, D. Zeinalipour-Yazti, 27th USENIX Large Installation System Administration Conference (LISA'13), Washington D.C., USA, Nov. 3–8, 2013.
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1440
Smartphone Testbeds• We developed a comprehensive architecture for
managing smartphone clusters through the web.– 40+ Android Devices, Real Sensors, Real Computing Stack– Different Connection Modalities: 3G, Wifi, Wired, Remote.

Static Androids Mobile Androids
SmartLab: http://smartlab.cs.ucy.ac.cy/
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1441
Smartphone Testbeds
Rent
See/Click
Shell
File Sys.
Automation
Debug
Data
Manage
SmartLab http://smartlab.cs.ucy.ac.cy/
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1442
Mockup Experiments
“Sensor Mockup Experiments with SmartLab", Demo at 13th ACM Intl. Conference of Information Processing in Sensor Networks (IPSN'14), Berlin, Germany, 2014.
"Managing big data experiments on smartphones", Distributed and Parallel Databases (DAPD '14), Springer US, 2014 (accepted).
• A mockup enables testing of a design.– In our context, it refers to the
process of feeding a smartphone with recorded values.
– GPS, RSSI, Accelerometer, Compass, Orientation, Temperature, Light, Proximity, Pressure, Gravity, Altitude
– Enables us to test a system without a particular functionality (e.g., Altitude).
Video
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1443
Mockup Experiments
Crowdsource RSS of AP in
buildings
Benchmark Localization Algorithms
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1444
Mockup Experiments• Example Mockup Experiments
– A) Testing 3 localization algorithms on different phones.– B) Map simulation on 8 devices for faster simulation.
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1445
Presentation Outline• Indoor Data Management
– Introduction– Location– Privacy– Modeling– Testbeds– Latest: Big-data, Device Diversity,
Prefetching Radiomaps.
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1446
Big Data Processing• Logging “big” quantities of RSSI fingerprints in the cloud,
calls for scalable processing architectures.– Historic RSSI for buildings (Offline Data)– Online RSSI that arrive from Crowdsourcers (Online Data)
• Apache Hadoop is nowadays widely endorsed by the industry and academia for offline processing of data using the Map/Reduce programming paradigm.
• Newer trends provide:• performance
abstractions.• In-Memory
processing concepts
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1447
• Massively process RSS log traces to generate a valuable Radiomap
• Processing current logs in Anyplace for a single building takes several minutes!
• Challenges in MapReduce:– Collect Statistics (count,
RSSI mean and standard deviation)
– Remove Outlier Values.– Handle Diversity Issues
Big Data Processing
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1448
• Quality: Unreliable Crowdsourcers, Multi-device Issues, Hardware Outliers, Temporal Decay, etc.– Remark: There is a
Linear Relation between RSS values of devices.
– Challenge: Can we exploit this to align reported RSS values?
"Crowdsourced Indoor Localization for Diverse Devices through Radiomap Fusion", C. Laoudias, D. Zeinalipour-Yazti and C. G. Panayiotou, "Proceedings of the 4th Intl. Conference on Indoor Positioning and Indoor Navigation" (IPIN '13), Montbeliard-Belfort France, 2013.
Device Diversity
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1449
Prefetching Radiomaps
• Problem: When a users moves inside an indoor space connectivity might be lost – intermittent connectivity.– WiFi AP out of range.
• As such, continuous localization with input from the IPS is a challenging task.
• Preloading the complete building or area map (like in GPS) is difficult due to scale and due to frequently updated data (by crowdsourcers)
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1450
Prefetching Radiomaps• Preprocessing:
A. Cluster Fingerprints
B. Use historic movement data
or building-rank to build
probability transition graph.
• Task:– Given a user at a position
with network connectivity exploit transition graph to compute the next cluster of fingerprints to download?
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Talk at Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia, October 2, 2014.
Indoor Data Management: Status and Challenges
Thanks – Questions?Demetris Zeinalipour
Data Management Systems Laboratory
Department of Computer Science
University of Cyprus
http://dmsl.cs.ucy.ac.cy/
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1452
Crowd Micro-blogging
• Social Media (Facebook,Linked-in,Twitter) utilize a Social Graph (friendship, follower, followee) to map the relationships between users.
• Challenges:– Applications many times require location-based
rather than social-based interactions, e.g.,• Send out Help message to closest neighbors.• Car-to-Car communication.
– Location-based services suffer from bootstrapping• e.g., Check in to Foursquare and find nobody else there
– Interacting with the Crowd, calls for stronger Privacy!
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1453
Crowd Micro-blogging• We developed an experimental social network after
receiving an Industrial Award by the Appcampus Program (Microsoft, Nokia & Aalto, Finland).– Ranked among the 5 best apps of the given program among
3500 submissions.– A few thousand downloads and active users on our big-data
backend.
http://rayzit.com/
Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010
Demetris Zeinalipour, Skoltech, Moscow, Russia, 2/10/1454
• Rayzit User Map
Crowd Micro-blogging
Research: Paper currently under submission at a major Data Engineering conference in respect to “Distributed All K Nearest Neighbor Queries”