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With the ubiquity of mobile devices, <i>spatial crowdsourcing</i> is emerging as a new platform, enabling <i>spatial tasks</i> (i.e., tasks related to a location) assigned to and performed by human workers. In this paper, for the first time we introduce a taxonomy for spatial crowdsourcing. Subsequently, we focus on one class of this taxonomy, in which(More)
Mobile devices equipped with positioning capabilities (e.g., GPS) can ask location-dependent queries to Location Based Services (<i>LBS</i>). To protect privacy, the user location must not be disclosed. Existing solutions utilize a trusted anonymizer between the users and the LBS. This approach has several drawbacks: (<i>i</i>) All users must trust the(More)
Real-world road-planning applications often result in the formulation of new variations of the nearest neighbor (NN) problem requiring new solutions. In this paper, we study an unexplored form of NN queries named optimal sequenced route (OSR) query in both vector and metric spaces. OSR strives to find a route of minimum length starting from a given source(More)
There is currently great interest in building information mediators that can integrate information from multiple data sources such as databases or Web sources. The query response time in such mediators is typically quite high. We present an approach for optimizing the performance of information mediators by selectively materializing data. We first present(More)
In this paper, for the first time, we introduce the concept of Spatial Skyline Queries (SSQ). Given a set of data points <i>P</i> and a set of query points <i>Q</i> each data point has a number of derived spatial attributes each of which is the point's distance to a query point. An SSQ retrieves those points of <i>P</i> which are not dominated by any other(More)
In this paper we propose a fundamental approach to perform the class of Nearest Neighbor (NN) queries, the core class of queries used in many of the location-based services, without revealing the origin of the query in order to preserve the privacy of this information. The idea behind our approach is to utilize one-way transformations to map the space of(More)
A frequent type of query in spatial networks (e.g., road networks) is to find the K nearest neighbors (KNN) of a given query object. With these networks, the distances between objects depend on their network con-nectivity and it is computationally expensive to compute the distances (e.g., shortest paths) between objects. In this paper, we propose a novel(More)
Sensed data in Wireless Sensor Networks (WSN) reflect the spatial and temporal correlations of physical attributes existing intrinsically in the environment. In this article, we present the Clustered AGgregation (CAG) algorithm that forms clusters of nodes sensing similar values within a given threshold (spatial correlation), and these clusters remain(More)
— In Wireless Sensor Networks (WSN), monitoring applications use in-network aggregation to minimize energy overhead by reducing the number of transmissions between the nodes. We note that nearby sensor nodes monitoring an environmental feature (e.g., temperature or brightness) typically register similar values. In this paper, we propose Clustered(More)