Detection of stable mobile communities in vehicular Ad Hoc Networks

Abstract

A vehicular Ad Hoc Network (VANET) is a type of wireless network where nodes represent moving vehicles. Some VANET-based applications might require organising vehicles into groups (communities). However, the high mobility of the vehicles and their tendency to travel in clustered flows makes them a challenging subject for community detection. Communities should be formed on the fly, using only local knowledge about their neighbourhood, and evolve as vehicles move over time. The main goal of this paper is to evaluate if stable community detection is possible in highly dynamic VANETs. To do so, the SandSHARC algorithm is extended with two different stability metrics: link duration and mobility similarity. In order to evaluate the stability of the evolving mobile communities, new quantitative and qualitative metrics are proposed, and run simulations on two different VANET scenarios: highway and urban. We analyse how the two stability metrics improve the stability of the detected communities. The results demonstrate that stability depends on the mobility patterns of the underlying traffic network. The proposed method can be applied in a distributed manner and produces communities with robust communication links between members what makes it viable for VANET applications.

Análise da Dinamicidade Espacial e Temporal das Comunidades em Redes Veiculares

“…Grzybek et al [Grzybek et al 2014] estenderam o algoritmo SAw-SHARC para detectar comunidades estáveis em VANETs. Essa nova versão utiliza a durac ¸ão do link e a similaridade de mobilidade como métrica de estabilidade.…”

“…No entanto, a identificac ¸ão de comunidades em redes altamente dinâmicas, por exemplo as VANETs, ainda possui um número reduzido de estudos. Dentre os estudos descritos na Sec ¸ão 3, apenas o estudo desenvolvido por Grzybek et al [Grzybek et al 2014] aborda este tema.…”

VANET Security and Privacy - An Overview

“…Also, this algorithm minimizes the message delay as compared to other algorithms proposed in this context. While, Grzybeket al in [57] proposed a stable community detection algorithm after considering the vehicle's dynamic motion, where authors evolved the Label Propagation Algorithm(LPA) community detection algorithm [58]with the Stability and Network Dynamics over a Sharper Heuristic for Assignment of Robust Communities (SandSHARC) [59]. Besides that, in [57], the authors evaluated their work by testing the stability of the detected community.…”

“…While, Grzybeket al in [57] proposed a stable community detection algorithm after considering the vehicle's dynamic motion, where authors evolved the Label Propagation Algorithm(LPA) community detection algorithm [58]with the Stability and Network Dynamics over a Sharper Heuristic for Assignment of Robust Communities (SandSHARC) [59]. Besides that, in [57], the authors evaluated their work by testing the stability of the detected community. Not only that, but alsoSingh and Sharma in [60] presented an Enhanced Attacked Packet Detection Algorithm (EAPDA) to mitigate various attacks, such as: DoS attack, which results in performance deterioration of VANET.…”