This repo contains the implementation for paper
Optimizing Sensor Deployment and Maintenance Costs in Large-Scale Environmental Monitoring
Xiaofan Yu, Kazim Ergun, Ludmila Cherkasova, Tajana Šimunić Rosing.
CODES+ISSS 2020. Published in TCAD 2020.
Test environment: MATLAB R2019b/R2020a.
Note: Need the Curve Fitting Toolbox for the fit function. Need the Bioinformatics Toolbox for the graphminspantree function.
The tutorial.m will walk you through all of our algorithms on the small dataset.
.
├── LICENSE
├── README.md // this file
├── SFO // the SFO toolbox by Krause et al. from FileExchange
├── alg // our algorithms
├── data-large // large dataset around LA after preprocess
├── data-small // small dataset around SD after preprocess
├── exp // scripts to run experiments
├── gp // sensing quality library based on Gaussian Process
├── libs // general library
├── lldistkm // distance calculation library from FileExchange
├── mlibs // maintenance cost library
└── tutorial.m
- Distance-Weighted Greedy (DWG) [Awerbuch et al. 1999].
- Information-Driven Sensor Querying (IDSQ) [Zhao and Guibas 2004].
- Padded Sensor Placements at Informative and cost-Effective Locations (pSPIEL) [Krause et al. 2011]. We download their implementation of Submodular Function Optimization toolbox from FileExchange here.
- Particle Swarm Optimization (PSO) [Clerc and Jennedy 2002].
- Artificial Bee Colony (ABC) Optimization [Karaboga and Basturk 2007].
For PSO and ABC, we devise the cost function for our sensor deployment problem in ./alg/CostFunction.m.
If you found the codebase useful, please consider citing
@article{yu2020optimizing,
title={Optimizing Sensor Deployment and Maintenance Costs for Large-Scale Environmental Monitoring},
author={Yu, Xiaofan and Ergun, Kazim and Cherkasova, Ludmila and Rosing, Tajana {\v{S}}imuni{\'c}},
journal={IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems},
volume={39},
number={11},
pages={3918--3930},
year={2020},
publisher={IEEE}
}MIT