Location Sensing Techniques and Applications

Location Sensing Techniques and Applications National Chiao Tung University Department of Computer Science Yu-Chee Tseng 2007/09/07

My Research Roadmap on WSN Signal Scrambling (IEEE TKDE*) Localization Data Clustering (MASS 2007) Beacon Movement (VTC 2007) Location Management (IEEE TMC, IJSN) Location Management (IEEE TMC, IJSN) Placement (IEEE TMC) Placement (IEEE TMC) Location Tracking & Deployment Location Tracking & Deployment k-Placement (IEEE TPDS*) k-Placement (IEEE TPDS*) Connectivity and Placement (ACM ToSN) Connectivity and Placement (ACM ToSN) WSN ConvergeCast (MobiWAC 2006) ConvergeCast (MobiWAC 2006) Comm. Protocol Comm. Protocol Orphan Problem (MSWiM 2007) Orphan Problem (MSWiM 2007) GeoAds (MASS 2007) GeoAds (MASS 2007) Emergency Guiding (IEEE Computer) Emergency Guiding (IEEE Computer) Applications & Systems Applications & Systems 3D Emergency Guiding (IJSN) 3D Emergency Guiding (IJSN) Surveillance: iMouse (IEEE Computer) Surveillance: iMouse (IEEE Computer) Energy Saving: iPower (IJSNET*) Energy Saving: iPower (IJSNET*)

<xn, yn> s i signal strength vector: [s1, s2, …, sm] <x2, y2> <xi, yi> <x1, y1> i 1 s real-time data Pattern-Matching Localization Overview access point (AP) Training Phase Positioning Phase avg. signal strength: [ i,1, i.2,…, i.m] training data training location <x1, y1>1 <x2, y2> 2 . . . <xn, yn>n Location Database Pattern-Matching Localization Algorithm <x, y>

Challenges with Pattern-Matching Localization • Unstable signal strengths and unpredictable multipath effect • High computation cost: huge location database to match, especially in large-scale environments • Environment changes and training cost • Maintenance (movement/lost of beacons) • Publications • S.-P. Kuo, B.-J. Wu, W.-C. Peng, and Y.-C. Tseng, "Cluster-Enhanced Techniques for Pattern-Matching Localization Systems", IEEE Int'l Conf. on Mobile Ad-hoc and Sensor Systems (MASS), 2007 • S.-P. Kuo, Y.-C. Tseng, and C.-C. Shen, "Increasing Search Space for Pattern-Matching Localization Algorithms by Signal Scrambling ", IEEE Asia-Pacific Wireless Communications Symposium, 2007. • S.-P. Kuo, Y.-C. Tseng, and C.-C. Shen, "A Scrambling Method for Fingerprint Positioning Based on Temporal Diversity and Spatial Dependency", IEEE Trans. on Knowledge and Data Engineering, submitted. • S.-P. Kuo, H.-J. Kuo, Y.-C. Tseng, and Y.-F. Lee, "Detecting Movement of Beacons in Location-Tracking Wireless Sensor Networks", IEEE VTC, 2007-Fall.

Localization: Signal Scrambling A Scrambling Method for Pattern-Matching Positioning Based on Temporal Diversity and Spatial Dependency

Difficulties • Multipath effect results in low accuracy for pattern-matchinglocalization. • Most of pattern-matching localization schemes adopt traditional classification, but ignore some unique features. • Ex. Continuous samples should have high similarity as well as diversity.

Observations • A positioning error could be generated by a small portion of interfered signal strengths. • Counting on one single observation is unreliable. • We can enlarge the search space by multiple continuous observations. • Continuous observations may have some degrees of • Temporal diversity: For a sequence ofobservations on a beacon, diversified signal strengths may be seen. • Spatial dependency: For a serious of estimated locations, they should be close each other.

Localization: Clustering ofLocation Database for pattern-matching localization in large-scale sensing field (such as a wireless city)

Challenges • Scalability problem when the field is large. • High computation cost in the positioning phase • Long system response time (critical to real-time applications) • To reduce computation cost in the positioning phase: • apply clustering technique to fragment database into a number of sets. • examine only one cluster in the positioning phase

<xn, yn> i s <x2, y2> <xi, yi> <x1, y1> i 1 s real-time data Cluster Scheme Overview access point (AP) Training Phase Positioning Phase avg. signal strength: [ i,1, i.2,…, i.m] signal strength vector: [s1, s2, …, sm] training data training location <x1, y1>1 <x2, y2> 2 . . . <xn, yn>n Location Database Pattern-Matching Localization Algorithm <x, y> C* Clustering

Localization: Beacon Movement Detection

Beacon Movement Detection Problem • Maintenance issue: beacon movement/failure • Ex: What happens if some beacons are moved by accident? • Goal: • Automatically detect the beacon movement events • Remove the data of these unreliable beacons from the database to improve accuracy Result: More serious localization error!!

System Model Positioning Procedure BMD Procedure ( t =0 denotes the initial time)

My Research Roadmap on WSN Signal Scrambling (IEEE TKDE*) Localization Data Clustering (MASS 2007) Beacon Movement (VTC 2007) Location Management (IEEE TMC, IJSN) Placement (IEEE TMC) Location Tracking & Deployment k-Placement (IEEE TPDS) Connectivity and Placement (ACM ToSN) WSN ConvergeCast (MobiWAC 2006) Comm. Protocol Orphan Problem (MSWiM 2007) GeoAds (MASS 2007) Emergency Guiding (IEEE Computer) Applications & Systems 3D Emergency Guiding (IJSN) Surveillance: iMouse (IEEE Computer) Energy Saving: iPower (IJSNET*)

Research Issues • Object Tracking • Event Detection • Target Classification • Location Estimation • Location Management • Tree-based update & query mechanisms • Single-sink WSNs & Multi-Sink WSNs • Deployment of WSNs • Placement • Dispatch • Single-level coverage & Multi-level coverage • Coverage and Connectivity • Coverage • Connectivity • Distributed protocols for ensuring both coverage and connectivity of a wireless sensor network • More general decentralized solutions • Do not rely on the assumption RC 2RS • Distributed protocols to determine and to control coverage and connectivity

Location Tracking & Deployment: “In-Network” Location Management

Location Management • Update and Query: • How to update the location information? • How to disseminate the queries?

Proposed Model

Location Tracking & Deployment: Sensor Placement

Deployment of a WSN for Single-Level Coverage • Sensor deployment is critical since it affects the cost and detection capability of a WSN. • A deployment should consider both coverage and connectivity, which decide by sensing distancers and communication distancerc. • Our contributions • Allow the sensing field to contain obstacles. • Allow the relationship of rc and rs to be arbitrary. • Complete solution: placement + dispatch

Sensor Placement Solutions • Partition the sensing field into sub-regions and then place sensors in each region. • Single-row regions • A belt-like area between obstacles • We can deploy a sequence of sensors to satisfy both coverage and connectivity. • Multi-row regions • We need multiple rows of sensors to cover such areas.

I A Sensor Dispatch Solutions • Centralized algorithm • Find a maximum-weightperfect matching in a weight complete bipartite graph • Distributed algorithm • Let sensors compete to move to their destinations • Existence of obstacles

Location Tracking & Deployment: Multi-level Placement of Sensors

2 1 1 3 2 2 1 Deployment of a WSN for Multi-Level Coverage • Multi-level coverage is essential for many protocols and applications in WSNs • Positioning protocols by triangulation • Fault tolerance on coverageor sensory data • Wakeup-sleep mechanism to extend the network’s lifetime • Our contributions • Allow the relationship of rc and rs to be arbitrary • Complete solution • Placement solution: interpolating scheme • Dispatch solution: competition-based scheme

regions that are NOT 3-covered Interpolating Placement Scheme: • 1-coverage placement: • duplicate scheme: 3 rows • 3-coverage placement? • 3-coverage placement: • - duplicate scheme: • 3 × 3 = 9 rows • - interpolatingscheme: • 3 × 2 + 1 = 7 rows

Publications • Journal Papers • C.-F. Huang, L.-C. Lo, Y.-C. Tseng, and W.-T. Chen “Decentralized Energy-Conserving and Coverage-Preserving Protocols for Wireless Sensor Networks”, ACM Trans. on Sensor Networks, Vol. 2, No. 2, 2006, pp. 182-187. • Y.-C. Wang, C.-C. Hu, and Y.-C. Tseng, “Efficient Placement and Dispatch of Sensors in a Wireless Sensor Network”, IEEE Trans. on Mobile Computing (to appear). (SCI) • C.-Y. Lin, W.-C. Peng, and Y.-C. Tseng, "Efficient In-Network Moving Object Tracking in Wireless Sensor Networks", IEEE Trans. on Mobile Computing, Vol. 5, No. 8, Aug. 2006, pp. 1044-56. (SCI) • C.-Y. Lin, Y.-C. Tseng, T.-H. Lai, and W.-C. Peng, ”Message-efficient In-network Location Management in a Multi-sink Wireless Sensor Network”, Int’l Journal of Sensor Networks (to appear). • Conference Papers • Y.-C. Wang, W.-C. Peng, M.-H. Chang, and Y.-C. Tseng, "Exploring Load-Balance to Dispatch Mobile Sensors in Wireless Sensor Networks", Int'l Conf. on Computer Communication and Networks (ICCCN), 2007. • Y.-C. Wang, C.-C. Hu, and Y.-C. Tseng, “Efficient Deployment Algorithms for Ensuring Coverage and Connectivity of Wireless Sensor Networks”, Wireless Internet Conf. (WICON), 2005. • C.-F. Huang, L.-C. Lo, Y.-C. Tseng, and W.-T. Chen, “Decentralized Energy-Conserving and Coverage-Preserving Protocols for Wireless Sensor Networks”, Int’l Symp. on Circuits and Systems (ISCAS), 2005. • C.-Y. Lin, Y.-C. Tseng, and T.-H. Lai, “Message-Efficient In-Network Location Management in a Multi-sink Wireless Sensor Network”, IEEE Int’l Conf. on Sensor Networks, Ubiquitous, and Trustworthy Computing, 2006. • C.-Y. Lin and Y.-C. Tseng, "Structures for In-Network Moving Object Tracking in Wireless Sensor Networks", Broadband Wireless Networking Symp. (BroadNet), 2004.

Communication Protocol: Convergecast

A wakes up to hear C’s beacon and report data To C To C Network Scenario ZigBee coordinator • In a tree network, routers can send regular beacons to support low duty cycle operations A’s beacon sche: Zzz .. Zzz …. Zzz .. C’s beacon sche:

Contributions • Define a minimum delay beacon scheduling (MDBS) problem for ZigBee tree-based WSNs • Prove MDBS problem is NP-complete • Find special cases in MDBS • Propose centralized and distributed algorithms, which are compliant to the ZigBee standard

Communication Protocol: Orphan Problem

Challenge • In ZigBee, when forming a network, devices are said to join the network if it can receive a network address • Each device tries to associate to the ZigBee coordinator or a ZigBee router • A ZigBee coordinator or router will decide whether to accept devices according to its capacity • The capacity of a ZigBee device relates to the ZigBee address assignment

ZigBee Address Assignment • In ZigBee, network addresses are assigned to devices by a distributed address assignment scheme • ZigBee coordinator determines three network parameters • the maximum number of children (Cm) of a ZigBee router • the maximum number of child routers (Rm) of a parent node • the depth of the network (Lm) • A parent device utilizes Cm, Rm, and Lm to compute a parameter called Cskip • which is used to compute the size of its children’s address pools

node B 7 An ZigBee Address Assignment Example Cskip=6 Total:21 20 0 1 7 13 19 For coord. A becomes an orphan node !!

A Simulation Result Dotted nodes are orphan nodes !! ZigBee network formation The proposed scheme

Contributions • The first work that models the orphan problem in ZigBee networks • This orphan problem is divided by two subproblems • The Bounded-Degree-and-Depth-Tree Formation (BDDTF) problem • The End-Device Maximum-Matching (EDMM) problem • Prove the BDDTF problem is NP-complete • Propose a network formation algorithm, which can effectively reduce the number of orphan devices

Publications • Y.-C. Tseng and M.-S. Pan, “Quick Convergecast in ZigBee/IEEE 802.15.4 Tree-Based Wireless Sensor Networks”, ACM Int’l Workshop on Mobility Management and Wireless Access (ACM MobiWac), 2006. • M.-S. Pan and Y.-C. Tseng, "The Orphan Problem in ZigBee-based Wireless Sensor Networks", ACM/IEEE Int'l Symp. on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM), 2007.

Location Sensing Techniques and Applications