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Scaling heterogeneous information systems (HIS) to thousands of sources poses particular challenges to source discovery. It requires a powerful formalism for describing the contents of the sources in a concise manner and for formulating compatible queries as well as a suitable structure for indexing and retrieving the source descriptions efficiently.

We propose an extended logic-based description formalism for large-scale HIS with structured sources and a shared ontology. The formalism refines existing approaches that describe the sources by constraints on the attribute value ranges in several ways: It allows for complex, nested descriptions based on defined classes. It supports alternative descriptions to express that a source may be discovered by different combinations of constraints. Finally, it allows to adjust between positive matching, similar to keyword-based discovery, and negative matching, as used in existing logic-based approaches.

We further propose the SDC-Tree for indexing such source descriptions. To allow for efficient discovery, the SDC-Tree features multidimensional indexing capabilities for the different attributes and the IS-A hierarchy of the shared ontology, but also incorporates the existence or absence of constraints. For this purpose, it supports three different types of node split operations which exploit the expressiveness of the description formalism. Therefore, we also propose a generic split algorithm which can be used with arbitrary ontologies.

Moving objects databases (MODs) have been proposed for managing trajectory data, an important kind of information for pervasive applications. To save storage capacity, a MOD generally stores simplified trajectories only. A simplified trajectory approximates the actual trajectory of the mobile object according to a certain accuracy bound.

In order to minimize the costs of communicating position information between mobile object and MOD, the trajectory simplification should be performed by the mobile object. To assure that the MOD always has a valid simplified trajectory of the remote object, we propose the generic remote trajectory simplification protocol (GRTS) allowing for computing and managing a simplified trajectory in such a system in real-time.

We show how to combine GRTS with existing line simplification algorithms for computing the simplified trajectory and analyze trade-offs between the different algorithms. Our evaluations show that GRTS outperforms the two existing approaches by a factor of two and more in terms of reduction efficiency. Moreover, on average, the reduction efficiency of GRTS is only 12% worse compared to optimal offline simplification.

Space-partitioned Moving Objects Databases (SP-MODs) allow for the scalable, distributed management of large sets of mobile objects' trajectories by partitioning the trajectory data to a network of database servers.

Processing a spatio-temporal query q therefore requires efficiently routing q to the servers storing the affected trajectory segments. With a coordinate-based query - like a spatio-temporal range query - the relevant servers are directly determined by the queried range. However, with trajectory-based queries - like retrieving the distance covered by a certain object during a given time interval - the relevant servers depend on actual movement of the queried object. Therefore, efficient routing mechanisms for trajectory-based queries are an important challenge in SP-MODs.

In this paper, we present the Distributed Trajectory Index (DTI) that allows for such efficient query routing by creating an overlay network for each trajectory. We further present an enhanced index called DTI+S. It accelerates the processing of queries on aggregates of dynamic attributes, like the maximum speed during a time interval, by augmenting DTI with summaries of trajectory segments. Our simulations with a network of 1000 database servers show that DTI+S can reduce the overall processing time by more than 98%.