Static, dynamic, and adaptive heterogeneity in distributed smart camera networks


We study heterogeneity among nodes in self-organizing smart camera networks, which use strategies based on social and economic knowledge to target communication activity efficiently. We compare homogeneous configurations, when cameras use the same strategy, with heterogeneous configurations, when cameras use different strategies. Our first contribution is to establish that static heterogeneity leads to new outcomes that are more efficient than those possible with homogeneity. Next, two forms of dynamic heterogeneity are investigated: nonadaptive mixed strategies and adaptive strategies, which learn online. Our second contribution is to show that mixed strategies offer Pareto efficiency consistently comparable with the most efficient static heterogeneous configurations. Since the particular configuration required for high Pareto efficiency in a scenario will not be known in advance, our third contribution is to show how decentralized online learning can lead to more efficient outcomes than the homogeneous case. In some cases, outcomes from online learning were more efficient than all other evaluated configuration types. Our fourth contribution is to show that online learning typically leads to outcomes more evenly spread over the objective space. Our results provide insight into the relationship between static, dynamic, and adaptive heterogeneity, suggesting that all have a key role in achieving efficient self-organization.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
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Additional Information: Funding: PiCS project and received funding from the European Union 7th Framework Programme under grant agreement n. 257906. http://www.epics-
Uncontrolled Keywords: distributed smart cameras,heterogeneity,learning,self-organization,variation,Control and Systems Engineering,Computer Science (miscellaneous),Software
Publication ISSN: 1556-4703
Last Modified: 08 Dec 2023 09:57
Date Deposited: 29 Jul 2015 10:15
Full Text Link: http://dl.acm.o ... 2790463.2764460
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2015-06
Authors: Lewis, Peter R. (ORCID Profile 0000-0003-4271-8611)
Esterle, Lukas
Chandra, Arjun
Rinner, Bernhard
Torresen, Jim
Yao, Xin



Version: Accepted Version

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