Descriptive Name Services for Large Internets

This thesis addresses the challenge of locating people, resources, and other objects in the global Internet. As the Internet grows beyond a million hosts in tens of thousands of organizations, it is increasingly difficult to locate any particular object. Hierarchical name services are frustrating, because users must guess the unique names for objects or navigate the name space to find information. Descriptive (i.e. relational) name services offer the promise of simple resource location through a non-procedural query language. Users locate resources by describing resource attributes. This thesis makes the promise of descriptive name services real by providing fast query processing in large internets. The key to speed in descriptive query processing is constraining the search space using two new techniques, called an active catalog and meta-data caching. The active catalog constrains the search space for a query by returning a list of data repositories where the answer to the query is likely to be found. Components of the catalog are distributed indices that isolate queries to parts of the network, and smart algorithms for limiting the search space by using semantic, syntactic, or structural constraints. Meta-data caching improves performance by keeping frequently used characterizations of the search space close to the user, thus reducing active catalog communication and processing costs. When searching for query responses, these techniques improve query performance by contacting only the data repositories likely to have actual responses, resulting in acceptable search times. Even a request to locate a person with a popular name in the global name space can often be answered in seconds. The new techniques are integrated with existing data caching techniques through a single mechanism, called a referral. Referrals describe the conditions for using active catalog components, or re-using meta-data or data cache entries. Referrals form a DAG, called a referral graph, that directs query processing. The referral graph provides a uniform framework for identifying the specific system resources (e.g. cache entries or catalog components) that optimize processing for a query. It identifies search spaces that can be combined through intersection or union. It combines indices specific to organizations into a composite index for the global name space. It eliminates components with overlapping functions from query processing. The referral graph also provides a natural source of advice to users. Users who present expensive queries can be asked for specific attribute values to constrain the search for responses and lower processing cost. Referral graphs, an active catalog, meta-data and data caching are combined in the prototype descriptive name service called Nomenclator. In one measurement study, Nomenclator consistently improved the performance of descriptive queries in X.500. Another measurement study shows how Nomenclator uses a small investment of network bandwidth and server resources to improve the response time for a wide range of query sizes. An analytical modeling study shows that Nomenclator can amortize this investment over many queries to provide an overall reduction in system load and, as a consequence, better scaling and response time. Nomenclator provides a uniform interface to various name services, such as X.500 and the Ninth Edition Unix Name Service from Bell Labs. Nomenclator is simple to extend to include new name services.