A Novel Model for Vehicular Delay Tolerant Networks using Deterministic Bundle Relaying Scheme

Pradeep Kumar Tiwari, Shiv Prakash, Animesh Tripathi, Mohammad Aljaidi, Narendra Kumar Shukla, Omprakash Kaiwartya, Rupak Kharel

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The traditional bundle relaying scheme rarely utilizes the impact of selfish nodes in Vehicular Delay Tolerant Networks (VDTNs) that may not be able to transmit messages to other nodes because of limited resources in the road transport system. Here the Railway Transport System (RTS) is used to transfer the data from one end to another end into the network. In RTS, the proposed approach utilizes stationary nodes deployed along the railway tracks (usually at railway stations) with a large memory size, known as Track Side Units (TSUs), and mobile nodes which are trains equipped with devices having large buffer capacity and message relaying capability. In this paper, the VDTN scenario is developed using RTS in which all nodes have high buffer capacity and power availability hence storage and transfer of message bundles will be done through all nodes. Further, this paper proposed a novel model for transmitting data in VDTN environment using an Efficient Deterministic Bundle Relaying Scheme with Bulk Bundle Release (DBRS-BBR). To validate this, a mathematical model of queuing processes, M/G/1: FIFO/∞ /∞ , is applied at the TSUs and mobile units, and a Deterministic Scheduling technique is applied for relaying the bundles. To evaluate the proposed DBRS-BBR scheme, different performance measures are used, including Mean Queueing Delay, Mean Transit Delay, and Mean End-To-End Delay. This proposed scheme has the potential to improve message bundle transmission in remote areas and it outperforms the existing Probabilistic Bundle Relaying Scheme with Bulk Bundle Release (PBRS-BBR) in terms of various performance measures.

Original languageEnglish
Article number10530020
Pages (from-to)68916-68925
Number of pages10
JournalIEEE Access
Early online date13 May 2024
Publication statusPublished - 22 May 2024

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