When cars start gossiping

Costa, Paolo; Gavidia, Daniela; Koldehofe, Boris; Miranda, Hugo; Musolesi, Mirco; Riva, Oriana

doi:10.1145/1435467.1435468

Cited by 16 publications

(7 citation statements)

References 18 publications

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“…Implementing gossiping with the MRec update rule shows significant reductions in selfishness and is equivalent to increasing the visibility of interactions (for example, by increasing network connectivity). Gossiping has been applied successfully within the specific topological challenges of VANETs (Bako et al ; Costa et al ) and MANETs (Buchegger, ) and also within the domain of reputation mechanisms (Bachrach et al ; Mundinger and Le Boudec, ). Our results with no observability demonstrate the challenges of supporting cooperation in systems with low interaction visibility.…”

Section: Discussionmentioning

confidence: 99%

Robust Reputation in Decentralized Markets

Franks

Griffiths

2014

Computational Intelligence

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Establishing cooperation and protecting individuals from selfish and malicious behavior are key goals in open multiagent systems. Incomplete information regarding potential interaction partners can undermine typical cooperation mechanisms such as trust and reputation, particularly in lightweight systems designed for individuals with significant resource constraints. In this article, we (i) propose extending a low-cost reputation mechanism to use gossiping to mitigate against the effect of incomplete information, (ii) define four simple aggregation strategies for incorporating gossiped information, and (iii) evaluate our model on a variety of synthetic and real-world topologies and under a range of configurations. We show that (i) gossiping can significantly reduce the potentially detrimental influence of incomplete information and the underlying network structure on lightweight reputation mechanisms, (ii) basing decisions on the most recently received gossip results in up to a 25% reduction in selfishness, and (iii) gossiping is particularly effective at aiding agents with little or no interaction history, such as when first entering a system.

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Section: Discussionmentioning

confidence: 99%

Robust Reputation in Decentralized Markets

Franks

Griffiths

2014

Computational Intelligence

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“…Additionally the dynamic behaviors of the vehicles and the sparsely connected networks introduce new problems. However it is already shown that Gossip-based (Epidemic) protocols are effective to solve these problems and provide reliable and efficient communication [13].…”

Section: Related Workmentioning

confidence: 99%

EpiDOL: Epidemic Density Adaptive Data Dissemination Exploiting Opposite Lane in VANETs

Nizamoglu

Coleri

Özkasap

2013

Lecture Notes in Computer Science

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Abstract. Vehicular ad-hoc networks (VANETs) aim to increase the safety of passengers by making information available beyond the driver's knowledge. The challenging properties of VANETs such as their dynamic behavior and intermittently connected feature need to be considered when designing a reliable communication protocol in a VANET. In this study, we propose an epidemic and density adaptive protocol for data dissemination in vehicular networks, namely EpiDOL, which utilizes the opposite lane capacity with novel probability functions. We evaluate the performance in terms of end-to-end delay, throughput, overhead and usage ratio of the opposite lane under different vehicular traffic densities via realistic simulations based on SUMO traces in ns-3 simulator. We found out that EpiDOL achieves more than 90% throughput in low densities, and without any additional load to the network 75% throughput in high densities. In terms of throughput EpiDOL outperforms the Edge-Aware and DV-CAST protocols 10% and 40% respectively.

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“…These protocols are also known as gossip based and follow the natural spread of a disease or a rumor: a node owning a piece of information may selectively broadcast it to a subset of its neighbors, which in turn will further propagate it [3] [4]. The evaluation of the behavior of a VANET application is strictly related to the mobility scenario used in the simulations [1] [6]. However, no previous work has quantified the impact of mobility scenarios and other VANET characteristics on the epidemic diffusion of data.…”

Section: Data Dissemination In Vanetmentioning

confidence: 99%

Epidemic information diffusion in realistic vehicular network mobility scenarios

Barberis

Malnati

2009

2009 International Conference on Ultra Modern Telecommunications &Amp; Workshops

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Epidemic or gossip-based algorithms have been proposed for data dissemination in vehicular networks. Due to the unfeasibility of deploying large size vehicular networks, the performance evaluation of these algorithms is usually based on simulations. However, most literature works present experimental results based on hyper-simplified and non-realistic mobility scenarios or do not adequately describe the simulation setup. In this paper, we investigate the impact that road-network and vehicle density have on the performance of epidemic dissemination and the correlation between these factors and other simulation parameters, such as percentage of equipped vehicles, message expiration time, scheduling algorithm for data retransmission and number of circulating messages. We argue that, given the high sensitivity of this kind of approach to mobility scenarios, it would be useful to define a set of them to be used as a reference for evaluating different systems. Furthermore, from our simulations, we can state that, although epidemic diffusion does not guarantee data distribution to all network nodes, its simplicity and lack of infrastructure make it suitable for distributing real-time traffic or viability data in most mobility scenarios.

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When cars start gossiping

Cited by 16 publications

References 18 publications

Robust Reputation in Decentralized Markets

Robust Reputation in Decentralized Markets

EpiDOL: Epidemic Density Adaptive Data Dissemination Exploiting Opposite Lane in VANETs

Epidemic information diffusion in realistic vehicular network mobility scenarios

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