CrowdOp: Query Optimization For Declarative Crowd sourcing Systems - Coimbatore

ABSTRACT
We study the query optimization problem in declarative crowdsourcing systems. Declarative crowd sourcing is designed to hide the complexities and relieve the user the burden of dealing with the crowd. The user is only required to submit an SQL-like query and the system takes the responsibility of compiling the query, generating the execution plan and evaluating in the crowd sourcing marketplace. A given query can have many alternative execution plans and the difference in crowd sourcing cost between the best and the worst plans may be several orders of magnitude. Therefore, as in relational database systems, query optimization is important to crowdsourcing systems that provide declarative query interfaces. In this paper, we propose CROWDOP, a cost-based query optimization approach for declarative crowdsourcing systems. CROWDOP considers both cost and latency in the query optimization objectives and generates query plans that provide a good balance between the cost and latency. We develop efficient algorithms in the CROWDOP for optimizing three types of queries: selection queries, join queries and complex selection-join queries. We validate our approach via extensive experiments by simulation as well as with the real crowd on Amazon Mechanical Turk.

For more details, Contact
ph:9095395333,9159115969

Office Address:
LansA Informatics Pvt Ltd,
165, 5th Street, Cross cut road,
Gandhipuram, Coimbatore-641012