Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Colloquium: Department of Computer Science, University of Cyprus, Room 148, Building 12 (FST-01), 09:15-10:15, Thursday, Oct. 11, Querying Sensor Data in Smartphone Networks Demetris Zeinalipour Department of Computer Science University of Cyprus Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ current : The Post-PC Era Oct. 8, The Economist. "Beyond the PC" 02/2012: Canalys DeviceShip Annual growth Smartphones % Total PCs % - Notebooks % - Desktops % - Tablets % - Netbooks % 06/2012: IDC 1.6 B mobiles phones shipped in ( Gartner: PCs in use will reach 2B in 2014! 1.7 B units in (61% Android, 20.5% iOS, 5.2% Win) 2.2 B units in (53% Android, 19.2% iOS, 19% Win) Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Smartphones Smartphone: a mobile device (phone, tablet, slate) that offers more computing ability than a basic feature phone (e.g., one running JavaME) and a dumb phone. Computing Ability: CPU, Memory & Storage, Networking, Sensing. Examples: Motorola Atrix 4G / LG OPTIMUS G CPU: 1 Ghz Dual core / 1.5Ghz Quad-core (Qualcomm Snapdragon S4) RAM & Flash: 1GB & 48GB / 2GB & 32GB Networking: WiFi, 3G (Mbps) / 4G (100Mbps1Gbps) Sensing: Proximity, Ambient Light, Accelerometer, Microphone, Geographic Coordinates based on AGPS (fine), WiFi or Cellular Towers (coarse), Camera (13MB!) Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Smartphones: Networking Wireless Data Transfer Rates Plot Courtesy of H. Kim, N. Agrawal, and C. Ungureanu, "Revisiting Storage for Smartphones", The 10th USENIX Conference on File and Storage Technologies (FAST'12), San Jose, CA, February *** Best Paper Award *** 4G ITU peak rates: 100 Mbps (high mobility, such as trains and cars) 1Gbps (low mobility, such as pedestrians and stationary users) Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Smartphone: Sensors (Internal) Camera: Find the right coupons on the right moment! Microphone: Medical Stethoscope. GPS/WIFI/Cell: Smartphone Social Networks Compass / Accelerometer: Augmented Reality Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Smartphone Sensors (External) Nike+Apple Body Sensors: ECG, etc. Movement Sensors for Athletes Urban Sensing: CO 2, etc. Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Smartphones: Sensors (External) Amateur "Space" Exploration Program with an iPhone! (www.brooklynspaceprogram.org) Capsule: 31KM | -70 C Courtesy of: windows2universe.org Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Smartphone = ~1M Applications Apple App Store: 700,000 apps Google Play Store: 675,000 apps Graphic Courtesy of: Cnet.com / September 27, 2012 Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ N Smartphones = ? Applications Smartphone Network: Many Smartphones sensing and communicating without explicit user interactions in order to realize a collaborative task. Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Smartphone Networks: The Past Mapping Road Traffic with fixed cameras & sensors mounted on roadsides? Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Smartphone Networks Graphics courtesy of: A.Thiagarajan et. al. Vtrack: Accurate, Energy-Aware Road Traffic Delay Estimation using Mobile Phones, In Sensys09, pages ACM, (Best Paper) MITs CarTel Group Received Signal Strength (RSS): power present in WiFi radio signal Mapping the Road traffic by collecting WiFi signals. Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Smartphone Networks Monitoring Urban Spaces Traffic Road Quality Air Quality UNSW), Noise Pollution (Earphone),... "Ear-Phone: An End-to-End Participatory Urban Noise Mapping System " Rajib Rana, Chun Tung Chou, Salil Kanhere, Nirupama Bulusu, and Wen Hu. In ACM/IEEE IPSN 10, SPOTS Track, Stockholm, Sweden, April NoiseMap Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Smartphone Networks Client/Cloud Architectures Cloud "Big-data" (NoSQL/NewSQL) Privacy Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Smartphone Networks Peer-to-Peer Architectures (e.g., SmartP2P) Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Smartphone Networks Hybrid Architectures SmartTrace, Proximity, BloomMap, etc. Query Processor Energy! Privacy! Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Data Management in Systems and Networks (Sensor, Smartphone, P2P, Crowds, ) Research Focus Word cloud on titles of venues I have published at. / wordle.net Distributed Query Processing, Storage and Retrieval Methods for Sensor, Smartphone and Peer-to-Peer Systems, Mobile and Network Data Management, Energy-aware Data Management. Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Research Focus Sensor Data Management (MINT, MicroPulse, KSpot, ETC, MHS, SenseSwarm, FlashSort, etc.) PC Co-Chair MDM'10, DMSN'10 (VLDB'10) | Contest Chair ICDM'10 | General Co-Chair MobiDE'10 (SIGMOD) PC Co-Chair MobiDE'09 (ACM SIGMOD) General Co-Chair DMSN'11 (VLDB'11) Smartphone Data Management (SmartTrace, Proximity, SmartLab, SmartP2P, Airplace, CrowdCast, BloomMap) Data Management in Systems and Networks 2013 Demo Co- Chair: MDM'13 1 st PhD Graduate (P. Andreou), EWSN'12 Dissertation Award. - MDM'12 Best Demo! - Industrial NRE with Taiwan Mult. Comp. Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ SmartTrace Publications Main Related Articles: [J14] "Crowdsourced Trace Similarity with Smartphones", Demetrios Zeinalipour- Yazti and Christos Laoudias and Costantinos Costa and Michalis Vlachos and Maria I. Andreou and Dimitrios Gunopulos, IEEE Transactions on Knowledge and Data Engineering (TKDE '12), IEEE Computer Society, Volume 99, Los Alamitos CA USA, [C31] "Disclosure-Free GPS Trace Search in Smartphone Networks", Christos Laoudias, Maria I. Andreou, Dimitrios Gunopulos, "Proceedings of the 2011 IEEE 12th International Conference on Mobile Data Management - Volume 01" (MDM '11), IEEE Computer Society, Pages: , Washington DC USA, ISBN: , [C30] "SmartTrace: Finding similar trajectories in smartphone networks without disclosing the traces", Constandinos Costa, Christos Laoudias, Demetrios ZeinalipourYazti, Dimitrios Gunopulos, "Proceedings of the 2011 IEEE 27th International Conference on Data Engineering" (ICDE '11), IEEE Computer Society, Pages: , Washington DC USA, ISBN: , Other Related Work: "Finding the K Highest-Ranked Answers in a Distributed Network", D. Zeinalipour-Yazti,, Z. Vagena, D. Gunopulos and V. Kalogeraki, V. Tsotras, M. Vlachos, N. Koudas, D. Srivastava, Computer Networks (ComNet), vol. 53, issue 9, pp , Elsevier Press, 2009. Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Talk Outline Introduction SmartTrace: Trajectory Similarity Framework for Smartphones System Model and Problem Formulation Background on Trajectory Similarity SmartTrace (ST) Algorithm SmartTrace Prototype Overview Conclusions & SmartLab Other Research and Future Directions Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ System Model and Problem Formulation Find the K most similar trajectories to Q without pulling together all traces at QN Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ A.Dont Disclose the Users Trajectory to QN Social sites are already undergoing significant privacy restructuring (e.g., google buzz, facebook) Trajectories are large (270MB/year with 2s samples) B.Minimize Net Traffic and Local Processing 3G/4G and WiFi traffic: i) depletes smartphone battery and ii) degrades network health* * In 2009 AT&Ts customers affected by iPhone release. Constraints and Objectives [J15] "Crowdsourcing with Smartphones", Georgios Chatzimiloudis, Andreas Konstantinides, Christos Laoudias, Demetrios Zeinalipour-Yazti, IEEE Internet Computing (IC '12), Special Issue: Sep/Oct Crowdsourcing, May IEEE Press, Volume 16, Pages: 36-44, * * * * Minimize Networking + Processing! Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Trajectory Similarity Search Query D = 7.3 D = 10.2 D = 11.8 D = 17 D = 22 Distance ? Problem: Compare the query with all distributed sequences and return the k most similar sequences to the query. Similarity between two objects A, B is associated with a distance function (see next) K Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Lp-norms are the simplest way to compare trajectories (e.g., Euclidean, Manhattan, etc.) Lp-norms are fast (i.e., O(n)), but inaccurate. No Flexible matching in time. (miss out-of-phase) No Flexible matching in space. (miss outliers) Background on Trajectory Similarity P=1 Manhattan P=2 Euclidean Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Longest Common Subsequence A Dynamic Programming algorithm for this problem requires O(|A|*|B|) time. However we can compute it in O(*min(|A|,|B|)) if we limit the matching within a time window of . A B ignore majority of noise match Time Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ LCSS(MBE Q, A i ): Bounding Above LCSS * Indexing multi-dimensional time-series with support for multiple distance measures, M. Vlachos, M. Hadjieleftheriou, D. Gunopulos, E. Keogh, In KDD Q AiAi 2 40 pts 6 pts : Minimum Bounding Envelope TIME X * Indexing multi-dimensional time-series with support for multiple distance measures, M. Vlachos, M. Hadjieleftheriou, D. Gunopulos, E. Keogh, In KDD 2003. Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Trajectory Similarity Function Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ Talk Outline Introduction SmartTrace: Trajectory Similarity Framework for Smartphones System Model and Problem Formulation Background on Trajectory Similarity SmartTrace (ST) Algorithm SmartTrace Prototype Overview Conclusions & SmartLab Other Research and Future Directions Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ SmartTrace Algorithm Outline An intelligent top-K processing algorithm for identifying the K most similar trajectories to Q in a distributed environment. Step A: Conduct an inexpensive linear-time LCSS(MBE Q,A i ) computation on the smartphones to approximate the answer. Step B: Exploit the approximation to identify the correct answer by iteratively asking specific nodes to conduct LCSS(Q, A i ). Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/ SmartTrace Algorithm (1/2) Input: Query Trajectory Q, m Target Trajectories, Result Preference K (K