RegReS: Adaptively Maintaining a Target Density of Regional Services in Opportunistic Vehicular Networks
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Peh_RegReS adaptively.pdf
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Author(s)
Koukoumidis, Emmanouil
Peh, Li-Shiuan
Martonosi, Margaret
Date Issued
March 2011
Journal
Proceedings of the IEEE International Conference on Pervasive Computing and Communications, IEEE PerCom 2011
Publisher
Institute of Electrical and Electronics Engineers
Citation
Koukoumidis, Emmanouil, Pei Li-Shiuan and Margaret Martonosi. "RegReS: Adaptively Maintaining a Target Density of Regional Services in Opportunistic Vehicular Networks." In Proceedings of the IEEE International Conference on Pervasive Computing and Communications, IEEE PerCom 2011, Renaissance Seattle Hotel, Seattle, Washington, March 21-25, 2011.
Version
Author's final manuscript
Abstract
Pervasive vehicle-mounted mobile devices are increasingly
common, and can be viewed as a large-scale ad
hoc network on which collaborative, location-based services
can be directly supported. In order to support such services
within a geographic region, a certain number of computational,
storage and sensing mobile devices need to be carriers of
the services. This paper introduces and evaluates Region-
Resident Services (RegReS), a middleware that supports such
regional services by maintaining, in a fully distributed fashion,
a targeted density of service carriers. Carriers collaborate
opportunistically to estimate the current service density in the
region and coordinate the spawning of new service carriers
when necessary. Unlike previous approaches that are static,
RegReS adapts to dynamic conditions such as node speed,
effectively maintaining the targeted density of service carriers
in highly volatile vehicular networks. Results from the ORBIT
testbed, using synthetic and real bus mobility traces, show that
RegReS adapts to different system configurations, preserving
the desired service density with less than 16% mean absolute
error. We deployed an outdoor collaborative parking availability
service atop RegReS and demonstrated RegReS’s ability to
maintain the target service density with only 10% error.
Description
URL to paper listed on conference program.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
http://www.percom.org/documents/PerCom2011-program.pdf
