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Optimizing Information Credibility in Social Swarming Applications
June 2012 (vol. 23 no. 6)
pp. 1147-1158
ASCII Text
x 
 
Bin Liu, Peter Terlecky, Amotz Bar-Noy, Ramesh Govindan, Micheal J. Neely, Dror Rawitz, "Optimizing Information Credibility in Social Swarming Applications," IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 6, pp. 1147-1158, June, 2012.
 
 
BibTex
x
 
@article{ 10.1109/TPDS.2011.281,
author = {Bin Liu and Peter Terlecky and Amotz Bar-Noy and Ramesh Govindan and Micheal J. Neely and Dror Rawitz},
title = {Optimizing Information Credibility in Social Swarming Applications},
journal ={IEEE Transactions on Parallel and Distributed Systems},
volume = {23},
number = {6},
issn = {1045-9219},
year = {2012},
pages = {1147-1158},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.281},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Parallel and Distributed Systems
TI - Optimizing Information Credibility in Social Swarming Applications
IS - 6
SN - 1045-9219
SP1147
EP1158
EPD - 1147-1158
A1 - Bin Liu,
A1 - Peter Terlecky,
A1 - Amotz Bar-Noy,
A1 - Ramesh Govindan,
A1 - Micheal J. Neely,
A1 - Dror Rawitz,
PY - 2012
KW - Discrete optimization
KW - stochastic optimization
KW - corroboration.
VL - 23
JA - IEEE Transactions on Parallel and Distributed Systems
ER -
 
Bin Liu, University of Southern California, Los Angeles
Peter Terlecky, CUNY Graduate Center, New York
Amotz Bar-Noy, Brooklyn College and CUNY Graduate Center, New York
Ramesh Govindan, University of Southern California, Los Angeles
Micheal J. Neely, University of Southern California, Los Angeles
Dror Rawitz, Tel-Aviv University, Tel-Aviv
With the advent of smartphone technology, it has become possible to conceive of entirely new classes of applications. Social swarming, in which users armed with smartphones are directed by a central director to report on events in the physical world, has several real-world applications: search and rescue, coordinated fire-fighting, and the DARPA balloon hunt challenge. In this paper, we focus on the following problem: how does the director optimize the selection of reporters to deliver credible corroborating information about an event. We first propose a model, based on common notions of believability, about the credibility of information. We then cast the problem posed above as a discrete optimization problem, prove hardness results, introduce optimal centralized solutions, and design an approximate solution amenable to decentralized implementation whose performance is about 20 percent off, on average, from the optimal (on real-world data sets derived from Google News) while being three orders of magnitude more computationally efficient. More interesting, a time-averaged version of the problem is amenable to a novel stochastic utility optimization formulation, and can be solved optimally, while in some cases yielding decentralized solutions. To our knowledge, we are the first to propose and explore the problem of extracting credible information from a network of smartphones.

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Index Terms:
Discrete optimization, stochastic optimization, corroboration.
Citation:
Bin Liu, Peter Terlecky, Amotz Bar-Noy, Ramesh Govindan, Micheal J. Neely, Dror Rawitz, "Optimizing Information Credibility in Social Swarming Applications," IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 6, pp. 1147-1158, June 2012, doi:10.1109/TPDS.2011.281
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