MoteLab: a wireless sensor network testbed
By Geoffrey Werner-Allen, Patrick Swieskowski, Matt Welsh. International Symposium on Information Processing in Sensor Networks, 2005
696 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/a2d96563783d86e9f908d22e49524851f0cd4a2d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Prabal Dutta
- Gilman Tolle
- Matt Welsh
- David E. Culler
- Yunhao Liu
- Jonathan Hui
- G. Mainland
- Kamin Whitehouse
In Computer Vision and Pattern Recognition
- G. Mainland
- Biswanath Mukherjee
- Dipak Ghosal
- Jennifer Yick
- Rohan Murty
- Greg Morrisett
- Abhimanyu Gosaint
- Kamin Whitehouse
In Electrical and Electronic Engineering
- Yunhao Liu
- Matt Welsh
- G. Mainland
- Prabal Dutta
- Kamin Whitehouse
- David E. Culler
- Biswanath Mukherjee
- Dipak Ghosal
Citations in the corpus
- Wearable Environmental Sensors and Infrastructure for Mobile Large-Scale Urban Deployment (2016, background): “Simultaneously, comprehensive courseware and sensor platforms have been developed to teach university students about sensing in the context of wireless sensor networks with an emphasis on the networking aspects [29] as well as an emphasis on sensor integration and signal processing [30].”
- SmartSantander: IoT experimentation over a smart city testbed (2014, methodology): “For example the KanseiGeni [12], SensLab [13] and iLab.”
- Does Wireless Sensor Network Scale? A Measurement Study on GreenOrbs (2011, methodology): “Researchers have designed and developed indoor medium-scale testbed such as MoteLab [26] and Kansei [8] that assist and accelerate deploying and evaluating sensor network applications.”
- Efficient network flooding and time synchronization with Glossy (2011, methodology): “7.2.1 Scenario and Metrics We use three different testbeds to evaluate Glossy: MoteLab [34], Twist [14], and a local one.”
- Firefly-inspired sensor network synchronicity with realistic radio effects (2005, methodology): “Our experiments ran on MoteLab [16], a wireless sensor network testbed consisting of 24 MicaZ motes distributed over one floor of our Computer Science and Electrical Engineering building.”
- PRISM: platform for remote sensing using smartphones (2010, background): “Motelab [41] and Kansei [19] provide a generic framework for web-based scheduling of tasks on dedicated sensor platforms.”
- Wireless sensor network survey (2008, positive): “MoteLab have been used to study newly developed protocols , signal strength analysis, and cluster analysis.”
- Trio: enabling sustainable and scalable outdoor wireless sensor network deployments (2006, background): “Indoor testbeds like MoteLab [23] and Mirage [4] use real radio hardware that provides much greater communications realism but does not capture the nuances of outdoor environments.”
- Flask (2008, methodology): “One of the authors has worked closely with vulcanologists to deploy sensor networks that collected real-world seismic data at Reventador (Werner-Allen et al. 2006) and Volc´an Tungurahua (Werner-Allen et al. 2005a), both active volcanoes in Ecuador.”
- CitySense: An Urban-Scale Wireless Sensor Network and Testbed (2008, methodology): “Apart from the well-known PlanetLab [24] and Emulab [30] systems, significant wireless and sensor testbeds include ORBIT [26], Kansei [5], MoteLab [29], Mirage [23], and Mint [6].”