John Heidemann / Papers / Data Muling with Mobile Phones for Sensornets

Data Muling with Mobile Phones for Sensornets
Unkyu Park and John Heidemann
USC/Information Sciences Institute

Citation

Unkyu Park and John Heidemann. Data Muling with Mobile Phones for Sensornets. Proceedings of the 9th ACM SenSys Conference (Seattle, Washington, USA, Nov. 2011), 162–175. [PDF] [alt PDF]

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.

Bibtex Citation

@inproceedings{Park11a,
  author = {Park, Unkyu and Heidemann, John},
  title = {Data Muling with Mobile Phones for Sensornets},
  booktitle = {Proceedings of the 9th ACM {SenSys} Conference },
  year = {2011},
  sortdate = {2011-11-01},
  project = {ilense, siss, cisoft},
  jsubject = {sensornet_sharing},
  pages = {162--175},
  address = {Seattle, Washington, USA},
  month = nov,
  publisher = {ACM},
  jlocation = {johnh: pafile},
  keywords = {data muling, sensornet, cisoft, gps},
  url = {https://ant.isi.edu/%7ejohnh/PAPERS/Park11a.html},
  pdfurl = {https://ant.isi.edu/%7ejohnh/PAPERS/Park11a.pdf},
  myorganization = {USC/Information Sciences Institute},
  copyrightholder = {ACM},
  copyrightterms = {
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   	the copies are not made or distributed for profit or
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   	print or the first screen in digital
   	media. Copyrights for components of this work owned
   	by others than ACM must be honored. Abstracting with
   	credit is permitted. 
   	otherwise, to republish, to post on servers, or to
   	redistribute to lists, requires prior specific
   	permission and/or a fee. Send written requests for
   	republication to ACM Publications, Copyright &
   	Permissions at the address above or fax +1 (212)
   	869-0481 or email permissions@acm.org.}
}

Copyright

Permission to make digital or hard copies of portions of this work for personal or classroom use is granted without fee provided that the copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page in print or the first screen in digital media. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Send written requests for republication to ACM Publications, Copyright & Permissions at the address above or fax +1 (212) 869-0481 or email permissions@acm.org.
Copyright © by John Heidemann