A preferential attachment model for primate social networks

Wildlife monitoring is an enormous organizational challenge due to the required time and effort for setting and maintaining it. It is particularly difficult when the observed species has a complex social hierarchy and different roles for the members in the social group. In this paper, we introduce a...

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Bibliographic Details
Published in:Computer networks (Amsterdam, Netherlands : 1999) Netherlands : 1999), 2015-01, Vol.76, p.207-226
Main Authors: Akbaş, Mustafa İlhan, Brust, Matthias R., Turgut, Damla, Ribeiro, Carlos H.C.
Format: Article
Language:English
Subjects:
Algorithms
Animal behavior
Animal monitoring
Attachment
Hierarchies
Mobility
Monitoring
Monkeys & apes
Networks
Preferential attachment
Primates
Sensors
Social networks
Studies
Wildlife management
Wireless networks
Wireless sensor networks
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Summary:Wildlife monitoring is an enormous organizational challenge due to the required time and effort for setting and maintaining it. It is particularly difficult when the observed species has a complex social hierarchy and different roles for the members in the social group. In this paper, we introduce an approach to model a primate social network. The primates have complex social behaviors and network structure. As a result, there is a need for realistic computational models to fully understand and analyze the social behavior of such animal groups. We propose a novel spatial cut-off preferential attachment model with a center of mass concept to model the characteristics of the primate groups and a role determination algorithm, which groups the primates into their roles in the society based on the data collected by the wireless sensor and actor networks (WSAN). The performance of the monitoring and role determination algorithms, the applicability of the network formation and the mobility models are evaluated through extensive simulations. The results show that the proposed primate group models deliver networks with properties similar to real-life primate groups in terms of social network characteristics.
ISSN:1389-1286
1872-7069
DOI:10.1016/j.comnet.2014.11.009