Challenges and Strategies in Location-Dependent Information Services for Mobile Users

1. Data management in location-dependent information services (LDIS)

2. LDIS: important class of context-aware application Reasons: • Advances in wireless networks • Personal portable devices • Location-identification techniques

3. Preliminaries Challenges: • Mobile environment constraints(scarce bandwidth, limited local resources, low-quality communication, frequent network disconnection) • Spatial data(answers vary with location) • User movement(considered for query scheduling and cache management)

4. Location models, query types, valid scopes Location models: • geometric model: set of coordinates • symbolic model: real-world entities Query types: • local queries: current location of user • Non-local queries: other location • simple queries: simple condition • general queries: complex condition Valid scopes: Area(s) within which the query result is valid Example: (nearby-restaurant, {C}) = {3,4}

5. Research issues In a wireless system, user can access data: • On-demand • Broadcast • Combination (1. and 2.) To each mode data caching can be applied

6. On-demand access(1) Client submits a request (query, location). Server locates data and send it to mobile client. Issues: • Data placement • Central database • Distributed placement • Data replication • Copies of the data  improve reliability

7. On-demand access(2) Issues: • Query scheduling • user change location, the answer might be invalid • solution: schedule queries that leave current answer’s valid scope (avoid rejecting and reprocessing) • Indexing • index searching  enhance query performance

8. Broadcast Data are broadcast on a public wireless channel  Users can access data simultaneously • Indexing on air • Safe battery power • Broadcast strategies • Single wireless channel • Wireless channel is divided into subchannels

9. Data caching Data is cached at mobile client  lower data transmission, improve data availability (by disconnection) Data become obsolete • Time-dependent cache invalidation • location-dependent cache invalidation Limited cache space • Cache replacement is needed

10. Cache invalidation time-dependent cache invalidation: • Data updated on the server, data by client become obsolete (time) location-dependent cache invalidation: • data become invalid because client changed location • solution: attach valid scope to data instance

11. Cache replacement The cache space is limited. Which instance should be replaced? Factors: • least access probability (traditional) • data distance • distance user location and valid scope • valid scope area • Larger the area  higher probability