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Unkyu Park

dblp:13/1981 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2011
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Internet of things and sensor networks · 91% Cellular and mobile networks · 9%

Topics — the 2 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks › delay tolerant networks
data muling
0.112011
Data muling with mobile phones for sensornets · SenSys 2011
Internet of things and sensor networks › wireless sensor network
sensor deployment
0.112011
Data muling with mobile phones for sensornets · SenSys 2011

Methods — techniques the papers use, named apart from their topics

opportunistic mobility · 0.1bluetooth · 0.1
YearPublicationVenuePosition
2011 Data muling with mobile phones for sensornets
abstract
Sensors are all around us, in buildings, vehicles and public places, from commodity thermostats to custom sensornets. Yet today these sensors are often disconnected from the world, either because they are distant from infrastructure, and wide-area networking (by 3G cellular, satellite, or other approaches) is too expensive to justify. Data muling makes communication cost-effective by leveraging short-range wireless and mobility, perhaps by zebras, buses or farmworkers. In this paper we propose that human-carried mobile phones can serve as data mules for sensornet deployments, exploiting ubiquity of mobile phones and human mobility to bring low-cost communication to sensors. We use two mobile phone datasets to show that Bluetooth can serve as a viable muling network, and humans already see many potential sensors regularly. We have implemented a mobile-phone-based data muling system, and used it in four sensornet deployments totaling ten months operation. We find that muling can be the only cost-effective option for rural deployments, where it is critical to monitoring remote sensor networks. We also show opportunistic mobility can collect data without any extra effort in residential and office environments. Finally, we systematically evaluate our deployments to understand how contact duration and data size interact, and to evaluate the effect of muling on phone batteries.
Unkyu Park, John S. Heidemann
SenSys1