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Sensors 2018, 18(8), 2731; https://doi.org/10.3390/s18082731

Distributed Egocentric Betweenness Measure as a Vehicle Selection Mechanism in VANETs: A Performance Evaluation Study

1
Institute of Computing (IC), University of Campinas (UNICAMP), 1251 Albert Einstein Av., Campinas, SP 13083-970, Brazil
2
Faculty of Business and Information Technology (FBIT), University of Ontario Institute of Technology (UOIT), 2000 Simcoe St N, Oshawa, ON L1H 7K4, Canada
*
Author to whom correspondence should be addressed.
Received: 24 July 2018 / Revised: 15 August 2018 / Accepted: 16 August 2018 / Published: 20 August 2018
(This article belongs to the Special Issue Algorithm and Distributed Computing for the Internet of Things)
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Abstract

In the traditional approach for centrality measures, also known as sociocentric, a network node usually requires global knowledge of the network topology in order to evaluate its importance. Therefore, it becomes difficult to deploy such an approach in large-scale or highly dynamic networks. For this reason, another concept known as egocentric has been introduced, which analyses the social environment surrounding individuals (through the ego-network). In other words, this type of network has the benefit of using only locally available knowledge of the topology to evaluate the importance of a node. It is worth emphasizing that in this approach, each network node will have a sub-optimal accuracy. However, such accuracy may be enough for a given purpose, for instance, the vehicle selection mechanism (VSM) that is applied to find, in a distributed fashion, the best-ranked vehicles in the network after each topology change. In order to confirm that egocentric measures can be a viable alternative for implementing a VSM, in particular, a case study was carried out to validate the effectiveness and viability of that mechanism for a distributed information management system. To this end, we used the egocentric betweenness measure as a selection mechanism of the most appropriate vehicle to carry out the tasks of information aggregation and knowledge generation. Based on the analysis of the performance results, it was confirmed that a VSM is extremely useful for VANET applications, and two major contributions of this mechanism can be highlighted: (i) reduction of bandwidth consumption; and (ii) overcoming the issue of highly dynamic topologies. Another contribution of this work is a thorough study by implementing and evaluating how well egocentric betweenness performs in comparison to the sociocentric measure in VANETs. Evaluation results show that the use of the egocentric betweenness measure in highly dynamic topologies has demonstrated a high degree of similarity compared to the sociocentric approach. View Full-Text
Keywords: ego-networks; sociocentric centrality measures; egocentric centrality measures; egocentric betweenness measure; vehicular ad hoc networks (VANETs); social network analysis (SNA) ego-networks; sociocentric centrality measures; egocentric centrality measures; egocentric betweenness measure; vehicular ad hoc networks (VANETs); social network analysis (SNA)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Akabane, A.T.; Immich, R.; Pazzi, R.W.; Madeira, E.R.M.; Villas, L.A. Distributed Egocentric Betweenness Measure as a Vehicle Selection Mechanism in VANETs: A Performance Evaluation Study. Sensors 2018, 18, 2731.

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