User-Centric Distributed Route Planning in Smart Cities based on Multi-Objective Optimization
The realization of edge-based cyber-physical systems (CPS) poses important challenges in terms of performance, robustness, security, etc. This paper examines a novel approach to providing a user-centric adaptive route planning service over a network of Road Side Units (RSUs) in smart cities. The key idea is to adaptively select routing task parameters such as privacy-cloaked area sizes and number of retained intersections to balance processing time, privacy protection level, and route accuracy for privacy-augmented distributed route search while also handling per-query user preferences. This is formulated as an optimization problem with a set of parameters giving the best result for a set of queries given system constraints. Processing Throughput, Privacy Protection, and Travel Time Accuracy were developed as the objective functions to be balanced. A Multi-Objective Genetic Algorithm based technique (NSGA-II) is applied to recover a feasible solution. The performance of this approach was then evaluated using traffic data from Osaka, Japan. Results show good performance of the approach in balancing the aforementioned objectives based on user preferences.
F. Tiausas et al., "User-Centric Distributed Route Planning in Smart Cities based on Multi-Objective Optimization," Proceedings - 2021 IEEE International Conference on Smart Computing, SMARTCOMP 2021, pp. 77 - 82, Institute of Electrical and Electronics Engineers (IEEE), Aug 2021.
The definitive version is available at https://doi.org/10.1109/SMARTCOMP52413.2021.00031
7th IEEE International Conference on Smart Computing, SMARTCOMP 2021 (2021: Aug. 23-27, Irvine, CA)
Keywords and Phrases
Distributed Route Planning; Edge Computing; Multi-Objective Optimization; NSGA-II; Smart Cities
International Standard Book Number (ISBN)
Article - Conference proceedings
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27 Aug 2021