1. 1/19 Michael Klein Universität Karlsruhe Lanes – A Lightweight Overlay for Service Discovery in Ad hoc Networks 3rd Workshop on Applications and Services in Wireless Networks (ASWN) Berne, Switzerland July 2-4, 2003 Michael Klein, Birgitta König-Ries, Philipp Obreiter Institute for Program Structures and Data Organization Chair: Prof. Peter C. Lockemann Universität Karlsruhe, Germany http://www.ipd.uni-karlsruhe.de/DIANE

2. 2/19 Michael Klein Universität Karlsruhe Scenario Query Service In: Course Out: Academic calendar Document Service In: -- Out: article on GROUP-BY operator Transformation Service In: Compressed File Out: File Gateway Service In: Access Data Out: Received Mails Where and when do my database classes take place? My Mails? More on SQL?

3. 3/19 Michael Klein Universität Karlsruhe Research Question  How can we  efficiently advertise and query  semantically complex services  in mobile ad hoc networks? Ancillary condition #1: Ontology-based service description Ancillary condition #2: Highly dynamic topology Limited device capabilities Goal: Service Discovery

4. 4/19 Michael Klein Universität Karlsruhe Ancillary Condition #1: Semantic Description myService:ServicemyProfile:InfoServiceProfile presents service Category „Information- Service“ domain „score.database“ docPar:DocumentParameter output doc:Document restrictedTo dc:Creator „Michael Klein“ 02.10.2002 dc:Created „ppt“ dc:Format „de“ dc:Language docInfo:Information dc:Title „Introduces the main concepts of JDBC „Intoduction to JDBC“ dc:Description contains theTopic: Topic dealsWith dc:Subject jdbc:JDBC refersTo Process… Example: Simple document service:  Non-linear structure  Needs domain dependent matching  Similarity matching necessary  Must be completed in a negotiation phase

5. 5/19 Michael Klein Universität Karlsruhe Ancillary Condition #2: Ad hoc Network a) Highly Dynamic Topology  Moving participants  Appearing obstacles  Logins / Logoffs  unpredictable failures b) Limited Device Capabilities  small energy reservoirs  limited radio range

6. 6/19 Michael Klein Universität Karlsruhe Service Discovery: Basic Approaches (1) Central Service Directory  proactive  not usable because of highly dynamic topology (ac #2a)  Special case: Extremely stable network regions Flooding  reactive  not usable because of high resource consumption (ac #2b)  Special case: Extremely instable network regions SLP Jini CORBA SSDP (UPnP) Webservices UDDI Napster FIPA Bluetooth JXTA Search Gnutella Ad-hoc-LEAP

7. 7/19 Michael Klein Universität Karlsruhe Service Discovery: Basic Approaches (2) Distributed Hash Tables  Use hash value of a service description as address for the storing node  Not usable for complex ontology-based descriptions (ac #1)  semantical closeness cannot be not preserved OceanStore Pastry Freenet Chord Globe Plaxton Tapestry CAN

8. 8/19 Michael Klein Universität Karlsruhe Basic Idea Basic Idea: Put logical structure on top of the existing network  which takes into consideration the complexity of the service descriptions (ac #1)  which cleverly routes service announce and query messages (ac #2b)  which can be efficiently adapted to changes of the underlying network (ac #2a) A B E C D A CE 23 1 physical network Overlay Overlay: no fixed graph, but a set of overlay conditions

9. 9/19 Michael Klein Universität Karlsruhe Content Addressable Network (CAN) 1 56 2 34 7 x y 1 2 3 5 4 6 7  Let D be an n-dimensional hypercuboid  Each node “owns” a non- empty hypercuboid of D  All these cuboids are disjoint and their union exactly yields D  Each node knows the addresses of all nodes with hypercuboids that are adjacent to the own one  Virtual Address Space

10. 10/19 Michael Klein Universität Karlsruhe Using 2D-CAN for Service Discovery  CAN’s hashing mechanism cannot be used (ac #1)  Separate service description from overlay  Only use fundamental semantics: Two dimensions: service announcement – service search  2D-CAN overlay: y-axis for service announcement x-axis for service search 1 56 2 34 7 x y service announcement service search

11. 11/19 Michael Klein Universität Karlsruhe Guaranteeing Structural Conditions of CAN General Problem: Algorithms developed for internet-based peer-to-peer networks  Login:  Split randomly chosen hypercuboid  structure is not adapted later on  Overlay links increasingly inefficient  Not aligned with physical topology  Detection of unreachable nodes:  Many PING messages by constantly checking at least 4 neighbors  Strict grid structure too rigid  Weaken it for ad hoc networks  Keep possibility to route messages efficiently

12. 12/19 Michael Klein Universität Karlsruhe Lanes: Idea 1 2 3 4 5 6 7 8 9 10 11 12  Give up fixed assignment in x direction  parallel Lanes of nodes  Within Lane: Fixed neighbors  From outside: All nodes within a lane are equal  use anycast routing in x direction any cast any cast

13. 13/19 Michael Klein Universität Karlsruhe Lanes: Service Trading 1 2 3 4 5 6 7 8 9 10 11 12 service announcement service search any cast any cast  Service Announcements  have long term effect  have to be persisted, maintained & removed (lifecycle)  need well known storing nodes  proactive y axis  Service Requests  one time action  no persistence necessary  reactive x axis

14. 14/19 Michael Klein Universität Karlsruhe Correcting Intended Structural Changes  Login N:  Insert N into lane that is physically close  Logoff N:  Delete service announcements of N in lane  Repair lane by linking N’s neighbors 1 2 3 4 5 6

15. 15/19 Michael Klein Universität Karlsruhe Correcting Unintended Structural Changes  Detection  Periodical PING message  (1) Node vanished  (2) Network partition  (3) Network reunion  Correction  (1) - Delete its announcements - Connect neighbors  (2) - Invalidate foreign announcemts - Assign unique partition IDs - Continue trading independently  (3) - Connect lanes at their ends - Reactivate announcements 1 2 3 4 5 PING LANE BROKEN LANE BROKEN 8 7 6 PING

16. 16/19 Michael Klein Universität Karlsruhe Optimizing the Structure  Optimizing Inner Lane Connections:  Detecting inefficiencies with the PING message  Correcting by logoff and login  Lane length:  Optimal lane length depends on  announce/request ratio  network stability  Determine dynamically by collecting profile information  Split or merge lanes in a zipper like fashion when necessary (topology-aware) 1 2 3 4 5 6 1 3 5 2 4 6

17. 17/19 Michael Klein Universität Karlsruhe Advantages of Lanes  Specialized for dynamic topologies  Fewer conditions  One periodical PING message only  Topology-aware algorithms  Algorithms for partition and reintegration  Algorithms for adapting the structure to the current local network profile  Fully decentralized, no flooding, no hashing, no leases  Independent from service description But: Specialized for service trading (  2 dimensions)  Compromise between loose and tight structure

18. 18/19 Michael Klein Universität Karlsruhe Outlook  Algorithms for self-tuning parameters  optimal lane length  optimal time between PING messages  etc.  Hierarchical lanes?  Complete regions act as single “node” within a lane  Implementation and evaluation  Currently being implemented within diploma thesis

19. 19/19 Michael Klein Universität Karlsruhe T H A N K S...for your attention! Do you have any questions? Further information: http://www.ipd.uni-karlsruhe.de/DIANE