Skyline queries on sensor networks have attracted much attention from the database research community due to their wide applications related to multi-criteria decision making. The existing methods use filters that are based on the data locality of sensor nodes and routing paths. However, they have two serious problems: i) unnecessary data transmission is still to frequent. ii) the processing cost of a continuous skyline query on high-dimensional data is very high. In this paper, we propose a new method that uses competitive mechanisms for processing continuous skyline queries. The proposed method dramatically reduces the data transmissions of sensors and quickly processes a continuous skyline query on high-dimensional data. An extensive performance study verifies the merits of our new method.

In this paper, we propose a novel filtering method for processing continuous skyline queries in wireless sensor network environments. The existing filtering methods on such environments use filters that are based on router paths. However, these methods do not have a major effect on reducing data for sensor nodes to transmit to the base station, because the filters are applied to not the whole area but a partial area. Therefore, we propose a novel and efficient method to dramatically reduce the data transmissions of sensors through applying an effective filter with low costs to all sensor nodes. The proposed effective filter is generated by using characteristics such as the data locality and the clustering of sensors. An extensive performance study verifies the merits of our new method.