Supporting Network Access and Service Location in Dynamic Environments

1. Supporting Network Access and Service Locationin Dynamic Environments Dirk Kutscher <dku@tzi.org> Jörg Ott <jo@netlab.hut.fi> Steffen Bartsch <sbartsch@tzi.org> TNC 2007 2007-05-23

2. Trends • Service location and selection a major issuefor WLAN service providers • Different use cases • Information about general coverage, roaming possibilities and tariffs • Facilitating automated access • Providing information for diagnosis and maintenance • Existing ways for service location and selection insufficient for mobile users • Fragmented information services (per provider) • Inadequate solutions for automated access(Google Maps mesh-ups etc.)  no offline usage! • Information often outdated

3. Example: FON Community WLAN Approach • Web-based information service with Google Maps-based visualization • Informational only • Information cannot be used for automated client device configuration • No relation to user’s current context • Position, required services

4. Selected Recent Developments • FON Connection Manager • Locate and automatically connect to FON Hotspots (Symbian S60) • DeviceScape • Centralized connectivity management approach • Mobile clients access DeviceScape information database through DNS requests • Providing WISP-specific information (how to log on) • Mainly targeting automated log-on • iPass Hotspot Finder • Offline hotspot finder for Windows XP, Vista • Pre-downloadable maps • Offline search based on different criteria

5. Shortcomings • Many provider-specific solutions • Not useful for general network service location • No structured update mechanisms • Users have to manually update the application/database • Focusing on WLAN network access • Other (related) services not covered • VoIP access, multimedia resources etc.

6. Service Maps: Main Concepts • Network Information Service for • Heterogeneous networks • Challenged environments • Large scale deployment • Different take on network service location • Receiver- and infrastructure-based filtering • Accommodate different network architectures • Main concept • Mobile nodes receive/request service information from different sources and construct network service map according to MN requirements • Support offline usage • Leverage locality of distribution networks (e.g., WLAN) and service scope

7. Service Map Distribution Architecture

8. Data Model

9. Filtering and Aggregation • Aggregation • E.g., provider-independent aggregators can combine Service Maps from multiple providers • Filtering • Different types of filter operations • Tag filter: specify service tags that have to be present in a service description • Location filter: Filter services relevant to a specific region • XPath filter: filter based on arbitrary XML content in service descriptions and refinements

10. Service Map URNs • Motivation: Transport-independent distribution can generate multiple copies • Globally unique identification for service maps required • Uniform Resource Name (URN) as an identification mechanism for service maps, fragments and refinements • Comparison rules (subset predicate) • Resolution Mechanism based onDynamic Delegation Discovery System (DDDS) • Obtain specific URI through domain-specific translation rules urn:svcmap:example.org:20061028:campus-wlan#coord=53.10663,8.852487;range=100 urn:svcmap:example.org:20061028:campus-wlan?6453#refinement-2343 urn:svcmap:example.org:20061128:wlan#xpath=//tariff[@type='volume']

11. Bootstrapping • Automating access to Service Map information in foreign networks • Identify active Service Map service, i.e., in a foreign hotspot • Obtain basic configuration information, e.g., Service Map URIs • Bootstrapping defined for different environments • Broadcast/Multicast: FLUTE session on standardized multicast address; simpler variant (no FLUTE) as a fallback • Unicast-only: IP-auto-configuration, resolving standardized bootstrapping URN through local DNS

12. Security • Authenticity and integrity fundamental Service Map properties • Have to preclude denial-of-service attacks by forged service information • Challenge: transceiver-model is based on changes to the information base by intermediaries • Filtering and aggregation must still be possible • Still, receivers cannot establish trust-relationship with every possible transceivers(scalability, operational issues) • Service Map approach:maintaining security propertiesof Service Maps fragmentsacross the distribution chain • Authenticated data structuresbased on Merkle hash trees • Implemented with XML Digital Signatures

13. Implementation • Infrastructure • Service Map distribution servers • Client software • Web-based client • Browser-based Service Map interface for online usage • Mobile client • Offline client for smaller devices, mobile phones

16. Experiences • Larger-scale campus WLAN application • Setup, operations, measurements • Enhancing connectivity in mobile scenarios • Employing service maps for scheduling network access • Simulations

17. Campus Scenario

18. Campus Evaluation • Bootstrapping in campus environment • Using FLUTE via IP-Multicast • Providing data on 400 APs • Reasonable bandwidths: 1kB – 64kB • Good performance:about 2 – 16s

19. Mobile Scenario Evaluation • Mobile user connectivity • WLAN emulation • Either with acquiring data on APs in proximity or with sensing and probing • Relatively simple connectivity algorithm • Still 10% increase in Internet connectivity

20. Access control + anonymization Data set matching + freshness handling Mapping reports to known hotspots Distribution Incoming database Dynamic database Service Maps Upload server Aggregator Integrator Service Map Sender Provider database HTTPS Service Map Transport U U U U U U U U Contribution

21. Hotspot DisplaysRevisited http://service-maps.net/spot-3faed

22. Conclusions • Automating access to WLAN hotspots is a major challenge for making evolving WLAN-based applications usable • First developments are becoming eminent • But: no provider-independent approach available today • Network Service Maps as a general approach:Application- and provider-independent, supporting different transport services and organizational configurations • Recent results: Large-scale operation • Leveraging community contributions through contribution interface for user-observed hotspots

23. http://service-maps.net/ Dirk Kutscher <dku@tzi.org>