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Lukas Esterle

Learning to be different: Heterogeneity and efficiency in distributed smart camera networks

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  • Peter R. Lewis, Birmingham University
  • ,
  • Lukas Esterle
  • Arjun Chandra, Universitetet i Oslo
  • ,
  • Bernhard Rinner, University of Klagenfurt
  • ,
  • Xin Yao, Birmingham University

In this paper we study the self-organising behaviour of smart camera networks which use market-based handover of object tracking responsibilities to achieve an efficient allocation of objects to cameras. Specifically, we compare previously known homogeneous configurations, when all cameras use the same marketing strategy, with heterogeneous configurations, when each camera makes use of its own, possibly different marketing strategy. Our first contribution is to establish that such heterogeneity of marketing strategies can lead to system wide outcomes which are Pareto superior when compared to those possible in homogeneous configurations. However, since the particular configuration required to lead to Pareto efficiency in a given scenario will not be known in advance, our second contribution is to show how online learning of marketing strategies at the individual camera level can lead to high performing heterogeneous configurations from the system point of view, extending the Pareto front when compared to the homogeneous case. Our third contribution is to show that in many cases, the dynamic behaviour resulting from online learning leads to global outcomes which extend the Pareto front even when compared to static heterogeneous configurations. Our evaluation considers results obtained from an open source simulation package as well as data from a network of real cameras.

TidsskriftInternational Conference on Self-Adaptive and Self-Organizing Systems, SASO
Sider (fra-til)209-218
Antal sider10
StatusUdgivet - 1 dec. 2013
Eksternt udgivetJa
Begivenhed2013 IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2013 - Philadelphia, PA, USA
Varighed: 9 sep. 201313 sep. 2013


Konference2013 IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2013
ByPhiladelphia, PA
SponsorIEEE Computer Society, College of Engineering at Drexel University, Lockheed Martin, Applied Communication Sciences, BAE Systems

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