Locating Data Sources in Large Distributed Systems

Querying large numbers of data sources is gaining importance due to increasing numbers of independent data providers. One of the key challenges is executing queries on all relevant information sources in a scalable fashion and retrieving fresh results. The key to scalability is to send queries only to the relevant servers and avoid wasting resources on data sources which will not provide any results. Thus, a catalog service, which would determine the relevant data sources given a query, is an essential component in efficiently processing queries in a distributed environment. This paper proposes a catalog framework which is distributed across the data sources themselves and does not require any central infrastructure. As new data sources become available, they automatically become part of the catalog service infrastructure, which allows scalability to large numbers of nodes. Furthermore, we propose techniques for workload adaptability. Using simulation and real-world data we show that our approach is valid and can scale to thousands of data sources.