Adaptive fault-tolerant data flooding for energy-aware sensor networks

Karzand, Mina; Rezaie, M.G.; Mansouri, V.S.

doi:10.1109/icisip.2005.1529427

Cited by 2 publications

(1 citation statement)

References 8 publications

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“…To facilitate data level distribution, Karzand et al 20 have proposed an energy efficient scheme that reduces the duty cycle of sensor nodes by introducing super‐nodes which respond to retransmission requests, whilst directed flood routing algorithms can be used to leverage the topology of the network and ensure rapid dissemination of sensed data 21–23. In general, when used for distributed inference, data flooding does not consider the heterogeneity of the network and results in high data dimensionality due the number of sources involved.…”

Section: Inferencing With Sensor Networkmentioning

confidence: 99%

Distributed inferencing with ambient and wearable sensors

Atallah

McIlwraith

Thiemjarus

et al. 2011

Wireless Communications

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Wireless sensor networks enable continuous and reliable data acquisition for real-time monitoring in a variety of application areas. Due to the large amount of data collected and the potential complexity of emergent patterns, scalable and distributed reasoning is preferable when compared to centralised inference as this allows network wide decisions to be reached robustly without specific reliance on particular network components. In this paper, we provide an overview of distributed inference for both wearable and ambient sensing with specific focus on graphical models-illustrating their ability to be mapped to the topology of a physical network. Examples of research conducted by the authors in the use of ambient and wearable sensors are provided, demonstrating the possibility for distributed, real-time activity monitoring within a home healthcare environment.

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Section: Inferencing With Sensor Networkmentioning

confidence: 99%