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Model-View Sensor Data Management in the Cloud

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Adaptive query execution for data management in the cloud

Anastasia Ailamaki, Debabrata Dash, Adrian Daniel Popescu

A major component of many cloud services is query processing on data stored in the underlying cloud cluster. The traditional techniques for query processing on a cluster are those offered by parallel DBMS. These techniques however, cannot guarantee high pe ...

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Top-k query processing is a fundamental building block for efficient ranking in a large number of applications. Efficiency is a central issue, especially for distributed settings, when the data is spread across different nodes in a network. This paper intr ...

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Towards Integrated and Efficient Scientific Sensor Data Processing: A Database Approach

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In this work, we focus on managing scientific environmental data, which are measurement readings collected from wireless sensors. In environmental science applications, raw sensor data often need to be validated, interpolated, aligned and aggregated before ...

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Nowadays, sensor data is generated in large amounts. Stor- ing or transmitting all the sensor’s measurements might not be the ideal choice because of the volume (and rate) at which it is generated. But we also cannot easily discard it, since ev- ery data m ...

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An Economic Model for Self-tuned Cloud Caching

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Cloud computing, the new trend for service infrastructures requires user multi-tenancy as well as minimal capital expenditure. In a cloud that services large amounts of data that are massively collected and queried, such as scientific data, users typically ...

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Graphical display for annual climate-based daylight simulation

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Due to daylight variability, a design cannot be thoroughly assessed using single-moment simulations, which is why we need dynamic performance metrics like Daylight Autonomy and Useful Daylight Illuminance. Going one step further, the annual variation in pe ...

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Modern scientific applications consume massive volumes of data produced by computer simulations. Such applications require new data management capabilities in order to scale to terabyte-scale data volumes [32, 10]. The most common way to discretize the app ...

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Building good sparse approximations of functions is one of the major themes in approximation theory. When applied to signals, images or any kind of data, it allows to deal with basic building blocks that essentially synthesize all the information at hand. ...

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Monadic Queries over Tree-Structured Data

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Monadic query languages over trees currently receive considerable interest in the database community, as the problem of selecting nodes from a tree is the most basic and widespread database query problem in the context of XML. Partly a survey of recent wor ...

2002