Discovering Representative Skyline Points over Distributed Data

Skyline queries help users make intelligent decisions over complex data. The main shortcoming of skyline queries is that the cardinality of the result set is not known a-priori. To overcome this limitation, the representative skyline query has been proposed, which retrieves a fixed set of k skyline points that best describe all skyline points. Even though the representative skyline has been studied before in centralized environments, this is the first paper that addresses efficient computation of the representative skyline in distributed systems. The distributed nature of the environment makes the task of discovering truly representative skyline points even more challenging. In this paper, we propose a novel framework for discovering the representative skyline over distributed data sources. Our experimental study demonstrates the efficiency and effectiveness of our framework.