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SmartTrace

ignore majority of noise. match. match. SmartTrace. Crowdsourced Trace Similarity with Smartphones. Costantinos Costa, Christos Laoudias, Demetrios Zeinalipour-Yazti and Dimitrios Gunopulos. University of Cyprus & University of Athens. Goals and Contributions. Similarity Comparison.

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SmartTrace

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  1. ignore majority of noise match match SmartTrace Crowdsourced Trace Similarity with Smartphones Costantinos Costa, Christos Laoudias, Demetrios Zeinalipour-Yazti and Dimitrios Gunopulos University of Cyprus & University of Athens Goals and Contributions Similarity Comparison Problem: Find the K users moving more similarly to a query trajectory Q, in a Smartphone Network. • Privacy: User trajectories and User identities are not disclosed to the Query Processor. • Performance: a) In-situ data storage of trajectories (on smartphone flash) and b) Query Processing using a Top-K Query Processing Algorithm that uses Bound Scores* • Flexible matching in time (ignore temporal noise) • Flexible matching in space (ignore spatial noise) • Ubiquity: Our system works both outdoors (using GPS) and indoors (using WLAN Signal Strength) The SmartTrace Framework System Model Performance Evaluation High Level Idea Smartphone Energy: ↓ 81% Android-based Smartphone Implementation Server Console “No Sharing” Policy SmartTrace Indoors (WLANRSS) Server• Ubuntu Linux• JDK 6, ~1500 LOC Client• HTC Desire smartphones• Android 2.1 (Eclair)• Google Map API• ~2500 LOC, ~250 lines XML• 510KB installation package APK• Runs on Dalvik VM (future: native C with Android NDK) SmartTrace Outdoors (GPS) SmartTrace Client GUI• Query devices by example• Plot and iterate through the responses using a variety of presentation styles• Configure parameters (e.g. K)• Control privacy settings• Online/Offline modes for recorded scenario playback• GPS/WiFi modes Indoor scenario at KIOS Research Center• 560m2 area, 3 APs, 1 Query (Q) RSS trajectory • 4 other (T1-T4) RSS trajectories, top-2 search• T2 and T3 correctly identified as top-2 answers

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