Title

A preferential attachment model for primate social networks

Authors

Authors

M. I. Akbas; M. R. Brust; D. Turgut;C. H. C. Ribeiro

Comments

Authors: contact us about adding a copy of your work at STARS@ucf.edu

Abbreviated Journal Title

Comput. Netw.

Keywords

Wireless sensor networks; Social networks; Mobility; Animal monitoring; Preferential attachment; WIRELESS SENSOR NETWORKS; MOUNTAIN GORILLAS; HOME-RANGE; ORGANIZATION; PATTERNS; BEHAVIOR; MACACA; Computer Science, Hardware & Architecture; Computer Science, Information; Systems; Engineering, Electrical & Electronic; Telecommunications

Abstract

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. (C) 2014 Elsevier B.V. All rights reserved.

Journal Title

Computer Networks

Volume

76

Publication Date

1-1-2015

Document Type

Article

Language

English

First Page

207

Last Page

226

WOS Identifier

WOS:000348882100014

ISSN

1389-1286

Share

COinS