A wide range of real-time applications process stream-based data. To process this stream-based data in an application-independent manner, many stream processing systems have been built. However, none of them reached a huge domain of applications, such as databases did. This is due to the fact that they do not consider the specific needs of real-time applications. For instance, an application which visualizes streambased data has stringent timing constraints, or may even need a specific hardware environment to smoothly process the data. Furthermore, users may even add additional constraints. E.g., for security reasons they may want to restrict the set of nodes that participates in processing. Thus, constraints naturally arise on different levels of query processing.In this work we classify constraints that occur on different levels of query processing. Furthermore we propose a scheme to classify the constraints and show how these can be integrated into the query processing of the distributed data stream middleware NexusDS.

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A steadily growing number of people using location based services (LBS) inflict massive query loads on the data tier of an LBS. As such queries usually possess considerable overlap, multiple cache nodes collaborating in a distributed spatial cache can provide scalable access to frequently used data. To preserve high throughput throughout the complete execution process, it is necessary to balance the accumulating load among the participating cache nodes. In this work, we identify three key-indicators to improve resource utilization during the load-balancing process: data skew, anticipated data access patterns and dynamic load peaks. For this reason, we introduce a comprehensive mathematical model to express the key-indicators as probability distribution functions. We fuse the different key-indicators into a single holistic distribution model. In the course of this, we devise a methodology from our holistic distribution model towards a distributed spatial cache offering improved load-balancing facilities.

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