1. 1 Locating Application Data Across Service Discovery Domains {csstrop,ben,muntz}@cs.ucla.edu {bisdik,parviz}@us.ibm.com {maria}@cs.columbia.edu MobiCom’01 {maria}@cs.columbia.edu Byoungjip Kim SSLab, EECS, KAIST April 22, 2003

2. 2 CONTENTS Introduction VIA Overview VIA Protocol Details Related Work Conclusions Critique

3. 3 ITRODUCTION Mobile Computing Pervasive Computing Thin Clients –PDAs, cellular telephones, sensors, etc. Service Discovery Architecture –To manage pervasive devices –Ex. SLP, Jini, Salutation, UPnP –service discovery protocol –but, local (cell topology) –service discovery domain

4. 4 INTRODUCTION (contd.) Problem – how to share data across service discovery domains Approach –1. Self-logging Client participation model Not sharable –2. Centralized index Infrastructure approach Not scalable Not reliable –3. Distributed indexes WASRV (1998, IETF) SDS (Mobicom’99, Berkeley) INS (OSR’99, MIT)

5. 5 VIA OVERVIEW Gateways Main Channel Metadata Tags –F1: (sslab) –F2: (sslab,ppigy) –F3: (sslab,bjkim) –F4: (sslab,piggy,p3.jpg) VIA –Verified Information Access –“way” in Latin Well Known Multicast Group (sslab, piggy, p1.jpg) (sslab, bjkim, b2.jpg) (sslab, piggy, p2.jpg) (sslab, bjkim, b3.jpg) (sslab, yjsong, y1.jpg) (sslab, piggy, p3.jpg) G1 G2 G3 G4 PDA G5 (sslab, piggy, p4.jpg)

6. 6 VIA OVERVIEW (contd.) Goal –To reduce irrelevant queries to the gateways Features –Hierarchical Scheme –Self-organizing of Gateways based on the types of queries depend on partial knowledge –Semantic Filtering get behind to avoid irrelevant queries –Data Centric Heuristic Criteria for Aggregation/Split –Hit ration: H = Q res /Q Aggregation is triggered when H < T1. –Filtering coefficient: F = Q c /Q root Split is triggered when H>T1, F>T2 –Heuristic mechanisms

7. 7 VIA PROTOCOL Spanning Tree Operations –Growth, Non-root failure, Root failure, and merging. Some basic notions –cluster table, edge set, rootside link –Messages : JOIN, LINK, QUERY, FAIL, ACCEPT, REFRESH Some useful technique –1. 128-bit randomly generated ID –2. proving (ping, RTT) –3. REFRESH message : heartbeat good scheme for the autonomy. –4. “token count” To avoid the congestion like “DOS” attack.

8. 8 VIA PROTOCOL (Contd.) Basic –Failure recovery algorithms are based on the growth algorithm. Heartbeat (REFRESH message) –Is is useful to detect connection failure.

9. 9 RELATED WORK Overlay Network –“test bed” “application-level infrastructure” –Adaptive Network : Odyssey (Michigan, ’99), CANS (NYU, ’01), etc. –Service Composition : Ninja (UCB, ’00), etc. VIAApplication-level multicast P2P file sharing EnvironmentMobile, Pervasivemaybe Mobile, not Pervasive maybe Mobile, not Pervasive GoalData Recovery, Sharing Content Distribution, Delivery Data Sharing Data Structure TreeMesh, TreeDHT ExampleWASRV (IETF, ’ 98) SDS (UCB, ’ 99) Yoid (ACIRI, ’ 99) Scattercast (UCB, ’ 99) Narada (CMU, ’ 00) NICE (UMD, ’ 02) Chord (MIT, ’ 01) Pastry (Rice, ’ 01) PAST (Rice, ’ 01)

10. 10 CONCLUSIONS Problem –To locate application specific data across service discovery domains. Solution –Multicast + VIA Goal of VIA –To reduce irrelevant queries to a gateway. VIA features –Hierarchy Scheme –Semantic Filtering –Self-organizing Mechanism –Data Centric Heuristic

11. 11 CRITIQUE Strong Points –Simple means against the complex distribution algorithm Proposal of Simple Self-organizing Mechanism Using Semantic Data Model (proper heuristic) Weak Points –VIA clusters rely on global multicast to bootstrap the cluster creation process. –As in any hierarchical scheme, top-level nodes act as “martyrs”. It must need a load balancing scheme for scalability. –Experiments are vulnerable to be doubted. There is no well-synthesized workload. New Idea –Collaboration based on “Reputation” of a node as another heuristic.

12. 12 CRITIQUE (contd.) New Idea

13. 13 Appendix 1 Metadata Tag Schema Query Example

14. 14 Appendix 2 Message Workload vs. Query Distribution

15. 15 Appendix 3 Workload distribution for 24 gateways, 6 cluster system