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Location-Aware m -Commerce

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Location-Aware m -Commerce

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  1. Mobile Consumers andLocation-Aware Information Management Managing Server-Based Location Information for Client-Based Location-Aware m-Commerce Applications of Location-Variant Mobile ConsumersJim WyseWireless Communications and Mobile Computing Research Centre (WCMCRC) Seminar Series, Faculty of Engineering and Applied Science, Memorial University, March 2010

  2. Location-Aware m-Commerce

  3. Mobile Commerce (m-Commerce) • transactions through communication channels that permit a high degree of mobility by at least one of the transactional parties.

  4. Location-Aware m-Commerce • m-business with location-referent transactions: transactions in which the geographical proximity of the transactional parties is a material transactional consideration. • Critical capability: location awareness. • Yuan and Zhang (2003): “location awareness … is a new dimension for value creation” in a wide variety mobile business applications.

  5. “Location-Awareness” The capability to obtain and use the geo-positions of the transactional parties to perform one or more of the CRUD (create, retrieve, update, delete) functions of data management.

  6. The Data Management Problem • Location-referent transactions are supported by proximity queries: What is my proximity to a goods-providing (or service-offering) location in a selected category? • A proximity query bears criteria that reference static attributes (e.g., hospital) and dynamic attributes (e.g., nearest). • Proximity queries are burdensome to conventional query resolution approaches (Nievergelt and Widmayer, 1997).

  7. Proximity Query Resolution  Proximity Portals The Client-Based i-DAR Prototype (Architecture: Client-Based Functionality, Server-Based Locations Repository)

  8. Web-Based i-Prox Prototype (Architecture: Functionality and Locations Repository are both Server-Based)

  9. The Problem (. . . and a Solution?)

  10. LinkcellsGeographical Space  Relational Space

  11. Location-Aware Linkcell Method • Transforms mu’s position (47.523° N, 119.137° W) into a linkcell (N47W119). • Initiates search sequence at mu’s linkcell {N48W119, N48W118, N47W118, • N46W118, ….} • Permits large numbers of locations to be excluded as proximity portal candidates. • Requires an appropriate linkcell ‘size’ (S) to give superior performance.

  12. Proximity Query Resolution Time Query Resolution Time (ms) Linkcell Size (S)

  13. Linkcell Performance Analyzer (LPA)

  14. Linkcell Optimality Interval

  15. Optimal Linkcell Size Solve …. PTC(S) = 1 – (1 – nTC/N)N/CS 0.6 . . . (A) . . . . for relational table names (linkcell “name increments” nTC is the number of locations in category, TC, N is total number of locations, and CS is the number of linkcells of size, S, created from the N locations.

  16. PTC(S) vs % within ILO

  17. Proximity Query Resolution Optimization

  18. Data Management Methods for Location-Based Services • Conventional (Enumerative) Methods • where C, U, D are ok but not R. • Linkcell-Based Methods • where R is ok but C, U, and D are burdened somewhat.

  19. MCRs and SCRs • Multiple Category Repositories (MCRs) • Single Category Repositories (SCRs) • Equation (A) applies to MCRs but not to SCRs • For SCRs, nTC = N  PTC(S) = 1, for all S.

  20. Single Category Repositories • For SCRs, it is hypothesized that optimal values are given by: • P(S) = 1 – (1 – S2/4A)N 0.6 . . . (B) • where A is the total geographical coverage, • S is the linkcell size, and • N is the number of locations. • Some preliminary results ……

  21. Figure 6

  22. 1. Location-Sensitive Mobile Services … incorporating … 2. Location-Aware Business Processes … supporting … 3. Location-Referent Transactions 1. Context-Sensitive Mobile Services … incorporating … 2. Context-Aware Business Processes … supporting … 3. Context-Referent Transactions Location-Based  Context-Based

  23. Notation Mobile User’s Situation  Set of Circumstances MUS  {C0, C1, . . ., CN} Let C0 represent a mobile user’s spatial circumstance, then MUS  {C0, C1, . . ., CN} requires a Context-Aware m-Business Service (also Location-Aware  Proximity Portal Problem) MUS  {C1, . . ., CN} requires a Context-Aware m-Business Service (not Location-Aware)

  24. MUS  {C0, C1} Context-Aware (Location-Aware) Special Case (the “Locationalized Business Directory” Case)  Generalize to {C0, C1, C2, …. CN}

  25. Prototypical Context-Aware System Context Server “contextualizes” Proto-Contexts

  26. Proto-Context Types 1. Non-Locationalized Proto-Contexts 2. Locationalized, Categorized Proto-Contexts (e.g., Locationalized “Classified” Business Directories) 3. Locationalized, Uncategorized Proto-Contexts (e.g., Specialized, Locationalized Business Directories a. k. a., Single Category Repositories)

  27. Linkcell Method (SCR) Reformulation Linkcell Construct. . . from: . . . to: • Linkcell Optimization. . . from: . . . to: P(S) = 1– (1 – nTC/N)N/CSP(S) = 1– (1 – S2/4A)N

  28. Proto-Context Data Management Methods 1. Non-Locationalized Proto-Contexts  use conventional CRUD methods 2. Locationalized, Categorized Proto-Contexts  use ‘standard’ Linkcell-Based CRUD methods 3. Locationalized, Uncategorized Proto-Contexts  use reformulated Linkcell-Based CRUD methods

  29. Recent Research Outputs Book Chapters – Professional/Academic Press Mobile Computing: Concepts, Methods, Tools, and Applications (2009) Advanced Principles for Improving Database Design, Systems Modeling, and Software Development (2008) Handbook of Research on Innovations in Database Technologies and Applications: Current and Future Trends (2009) Journal Article International Journal of Wireless and Mobile Computing (2009) Patent CIPO Patent 2508977 (2010)

  30. Contextualization Example MUS: Recreational Boater Proto-Context 1: Small Craft Harbours(Marine Services) Proto-Context 2: Smart Bay(Real-time Weather Conditions, etc.) Proto-Context 3: Public Libraries(Free Wireless Internet) Proto-Context 4: Lighthouses(Navigational Markers) Proto-Context 5: Municipalities(Information, Services) Generated Context: MobileMariner

  31. Mobile Consumers andLocation-Aware ( Context-Aware) Information Management Jim Wysewww.busi.mun.ca/jwyseThank you!! Wireless Communications and Mobile Computing Research Centre (WCMCRC) Seminar Series, Faculty of Engineering and Applied Science, Memorial University, March 2010

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