1. A Data Resolver Architecture for Discovering Pervasive Data Sources Matthew Denny Database Group U.C. Berkeley

2. Where are the Data Sources in Pervasive Applications? In traditional applications, the data sources are well defined and reside at well-known locations –SQL tables, web servers, SOAP/RPC apps, etc. In pervasive applications, neither property holds –Data sources are not at any given location (cell phones emitting diagnostic data roam about) –Data sources may be unreliable (sensors may lose power) –Data sources that are used by one application may use different protocols

3. Data Resolver Needed to Discover Pervasive Data Sources Data Resolver allows applications to discover data sources Data Sources send advertisements to the data resolver –Properties: name-value attribute pairs describing the data –Interfaces: descriptions on how to access the data Applications send specifications to query the data resolver –SQL or LDAP-like queries over the properties Application may want to know when data sources begin to or no longer match the query –Continuous Queries –Subscriptions to a data source’s advertisements

4. Implementation Plan Utilize standards for queries and advertisements –WSDL for service descriptions Scalability Problem: many rapidly updating data sources –Distributed “hybrid P2P” system with partial replication Each DR Node caches data as specified by its Master DR Node Specification –Any node can accept any ad or query Publish-Subscribe system used to route ads Query Containment Indexing (derived from predicate indexing research) used to route specifications