Centralised, Decentralised, and Self-Organised Coverage Maximisation in Smart Camera Networks

Lukas Esterle

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

When maximising the coverage of a camera network, current approaches rely on a central approach and rarely consider the decentralised or even self-organised potential. In this paper, we study the performance of decentralised and self-organised approaches in comparison to centralised ones in terms of geometric coverage maximisation. We present a decentralised and self-organised algorithm to maximise coverage in a camera network using a Particle Swarm Optimiser (PSO) and compare them to a centralised version of PSO. Additionally, we present a decentralised and self-organised version of ARES, a centralised approximation algorithm for optimal plans combining PSO, Importance Splitting, and an adaptive receding horizons at its core. We first show the benefits of ARES over using PSO as a single, centralised optimisation algorithm when used before deployment time. Second, since cameras are not able to change instantaneously, we investigate gradual adaptation of individual cameras during runtime. Third, we compare achieved geometrical coverage of our decentralised approximation algorithm against the centralised version of ARES. Finally, we study the benefits of a self-organised version of PSO and ARES, allowing the system to improve its coverage over time. This allows the system to deal with quickly unfolding situations.
Original languageEnglish
Title of host publication2017 IEEE 11th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)
PublisherIEEE
ISBN (Electronic)978-1-5090-6555-4
DOIs
Publication statusPublished - 19 Sep 2017
Event11th International Conference on Self-Adaptive and Self-Organizing Systems - University of Arizona, Tucson, United States
Duration: 18 Sep 201722 Sep 2017

Conference

Conference11th International Conference on Self-Adaptive and Self-Organizing Systems
CountryUnited States
CityTucson
Period18/09/1722/09/17

Fingerprint

Cameras
Approximation algorithms

Bibliographical note

© Copyright 2017 IEEE - All rights reserved

Cite this

Esterle, L. (2017). Centralised, Decentralised, and Self-Organised Coverage Maximisation in Smart Camera Networks. In 2017 IEEE 11th International Conference on Self-Adaptive and Self-Organizing Systems (SASO) IEEE. https://doi.org/10.1109/SASO.2017.9
Esterle, Lukas. / Centralised, Decentralised, and Self-Organised Coverage Maximisation in Smart Camera Networks. 2017 IEEE 11th International Conference on Self-Adaptive and Self-Organizing Systems (SASO). IEEE, 2017.
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Esterle, L 2017, Centralised, Decentralised, and Self-Organised Coverage Maximisation in Smart Camera Networks. in 2017 IEEE 11th International Conference on Self-Adaptive and Self-Organizing Systems (SASO). IEEE, 11th International Conference on Self-Adaptive and Self-Organizing Systems, Tucson, United States, 18/09/17. https://doi.org/10.1109/SASO.2017.9

Centralised, Decentralised, and Self-Organised Coverage Maximisation in Smart Camera Networks. / Esterle, Lukas.

2017 IEEE 11th International Conference on Self-Adaptive and Self-Organizing Systems (SASO). IEEE, 2017.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Esterle L. Centralised, Decentralised, and Self-Organised Coverage Maximisation in Smart Camera Networks. In 2017 IEEE 11th International Conference on Self-Adaptive and Self-Organizing Systems (SASO). IEEE. 2017 https://doi.org/10.1109/SASO.2017.9