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A Probabilistic and Traffic-Aware Bundle Release Scheme for Vehicular Intermittently Connected Networks

Delay-optimal data delivery in Vehicular Intermittently Connected Networks (VICNs) is challenging since vehicular traffic is affected by numerous recurring and completely random events. Some of these events cause breakdowns and jams while others subserve traffic stability. Researchers observed that...

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Bibliographic Details
Published in:IEEE transactions on communications 2012-11, Vol.60 (11), p.3396-3406
Main Authors: Khabbaz, M. J., Fawaz, W. F., Assi, C. M.
Format: Article
Language:English
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Summary:Delay-optimal data delivery in Vehicular Intermittently Connected Networks (VICNs) is challenging since vehicular traffic is affected by numerous recurring and completely random events. Some of these events cause breakdowns and jams while others subserve traffic stability. Researchers observed that mobile vehicles might be wisely exploited to connect two isolated, Stationary Roadside Units (SRUs). In this context, the design of effective delay-minimal data relaying strategies is receiving significant attention. However, many existing such schemes either do not adequately model vehicular traffic behaviours or adapt typical Internet packet-like forwarding protocols to VICNs. In contrast, this manuscript presents a concise, yet comprehensive study of vehicular traffic states based on which a "comme-il-faut" vehicular traffic model is established. This model captures the fundamental traffic characteristics and enables the selection of appropriate distributions for vehicular flow and speeds that parallel the realistic measurements made by traffic theorists. These distributions constitute the basis of a novel Probabilistic Bundle Release Scheme with Bulk Bundle Release (PBRS-BBR) that is proposed with the objective to minimize the average bundle delivery delay. An analytical queueing model is formulated to assess the performance of PBRS-BBR under medium-to-light vehicular traffic. Extensive simulations are conducted to prove the model's validity and accuracy.
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2012.082712.110473