Data-quality Guided Load Shedding for Expensive In-Network Data Processing

Peng, Lina; Candan, K. Selçuk

doi:10.1109/icde.2007.369003

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…For the experiments, we assume a 0% packet loss as default in order not to distort other factors which may be responsible for a reduction in tuple cardinality, such as load shedding (e.g., as in [31]) or sampling (e.g., as in [17]) which may be carried out by the data processing technique.…”

Section: Radio Packet Loss Ratementioning

confidence: 99%

SensorBench

Galpin

Stokes

Valkanas

et al. 2014

Proceedings of the 26th International Conference on Scientific and Statistical Database Management

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Wireless sensor networks enable cost-effective data collection for tasks such as precision agriculture and environment monitoring. However, the resource-constrained nature of sensor nodes, which often have both limited computational capabilities and battery lifetimes, means that applications that use them must make judicious use of these resources. Research that seeks to support data intensive sensor applications has explored a range of approaches and developed many different techniques, including bespoke algorithms for specific analyses and generic sensor network query processors. However, all such proposals sit within a multi-dimensional design space, where it can be difficult to understand the implications of specific decisions and to identify optimal solutions. This paper presents a benchmark that seeks to support the systematic analysis and comparison of different techniques and platforms, enabling both development and user communities to make well informed choices. The contributions of the paper include: (i) the identification of key variables and performance metrics; (ii) the specification of experiments that explore how different types of task perform under different metrics for the controlled variables; and (iii) an application of the benchmark to investigate the behavior of several representative platforms and techniques.

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Section: Radio Packet Loss Ratementioning

confidence: 99%

SensorBench

Galpin

Stokes

Valkanas

et al. 2014

Proceedings of the 26th International Conference on Scientific and Statistical Database Management

View full text Add to dashboard Cite

show abstract

“…There are also two representative studies [18], [16], on the quality of data (QoD) similar to the QoD defined in this paper. Among these, Ren et al proposed an algorithm to select the most related nodes as the active nodes to answer queries in a WSN to reduce the energy consumption of nodes without undermining the data quality much.…”

Section: Related Workmentioning

confidence: 99%