ConDense: Managing Data in Community-driven Mobile Geosensor Networks
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Efficiently querying data collected from Large-area Communitydriven Sensor Networks (LCSNs) is a new and challenging problem. In our previous works, we proposed adaptive techniques for learning models (e.g., statistical, non-parametric, etc.) from such dat ...
Conventional data warehouses employ the query-at-a-time model, which maps each query to a distinct physical plan. When several queries execute concurrently, this model introduces contention, because the physical plans—unaware of each other—compete for acce ...
Effectively managing the data generated by community-driven mobile geo-sensor networks is a new and challenging problem. One important step for managing and querying sensor network data is to create abstractions of the data in the form of models. These mod ...
We consider MapReduce workloads that are produced by analytics applications. In contrast to ad hoc query workloads, analytics applications are comprised of fixed data flows that are run over newly arriving data sets or on different portions of an existing ...
Conventional data warehouses employ the query- at-a-time model, which maps each query to a distinct physical plan. When several queries execute concurrently, this model introduces contention and thrashing, because the physical plans—unaware of each other—c ...
In standard database scenarios, an end-user assumes that all data (e.g., sensor readings) is stored in a database. Therefore, one can simply submit any arbitrary complex processing in the form of SQL queries or stored procedures to a database server. Data ...
Infinite nature of sensor data poses a serious challenge for query processing even in a cloud infrastructure. Model-based sensor data approximation reduces the amount of data for query processing, but all modeled segments need to be scanned, in the worst c ...
Infinite nature of sensor data poses a serious challenge for query processing even in a cloud infrastructure. Model-based sensor data approximation reduces the amount of data for query processing, but all modeled segments need to be scanned, in the worst c ...
With technological advances, the sources of available information have become more and more diverse. Recently, a new source of information has gained growing importance: sensor data. Sensors are devices sensing their environment in various ways and reporti ...
The automatic analysis of real-life, long-term behavior and dynamics of individuals and groups from mobile sensor data constitutes an emerging and challenging domain. We present a framework to classify people's daily routines (defined by day type, and by g ...
