@article{293ba7d623194e73b0fdee7b0d2004b2,
title = "Reliable sensor location for object positioning and surveillance via trilateration",
abstract = "Object positioning and surveillance has been playing an important role in various indoor location-aware applications. Signal attenuation or blockage often requires multiple local sensors to be used jointly to provide coverage and determine object locations via mobile devices. The deployment of sensors has a significant impact on the accuracy of positioning and effectiveness of surveillance. In this paper, we develop a reliable sensor location model that aims at optimizing the location of sensors so as to maximize the accuracy of object positioning/surveillance under the risk of possible sensor disruptions. We formulate the problem as a mixed-integer linear program and develop solution approaches based on a customized Lagrangian relaxation algorithm with an embedded approximation subroutine. A series of hypothetical examples and a real-world Wi-Fi access point design problem for Chicago O'Hare Airport Terminal 5 are used to demonstrate the applicability of the model and solution algorithms. Managerial insights are also presented.",
keywords = "Disruption, Lagrangian relaxation, Sensor location, Trilateration",
author = "Kun An and Siyang Xie and Yanfeng Ouyang",
note = "Funding Information: This research was financially supported in part by the U.S. National Science Foundation through Grant CMMI #1234085, the Roadway Safety Institute, the University Transportation Center for USDOT Region 5, which is funded by the United States Department of Transportation's Office of the Assistant Secretary for Research and Technology (OSTR), and by start-up grant E04001-2428391 from Monash University. The first author was a post-doctoral research associate at the University of Illinois when she started to work on this paper. Funding Information: This research was financially supported in part by the U.S. National Science Foundation through Grant CMMI # 1234085 , the Roadway Safety Institute, the University Transportation Center for USDOT Region 5, which is funded by the United States Department of Transportation{\textquoteright}s Office of the Assistant Secretary for Research and Technology (OSTR), and by start-up grant E04001-2428391 from Monash University . The first author was a post-doctoral research associate at the University of Illinois when she started to work on this paper. Publisher Copyright: {\textcopyright} 2017 Elsevier Ltd",
year = "2018",
month = nov,
doi = "10.1016/j.trb.2017.11.012",
language = "English (US)",
volume = "117",
pages = "956--970",
journal = "Transportation Research, Series B: Methodological",
issn = "0191-2615",
publisher = "Elsevier Limited",
}