Information from the abstract
Recent technological advancements have given rise to the intelligent transportation systems. This enhances the capability of nodes, through injection of intelligence, for the minimization of road accidents. To route safety messages, direction-aware greedy protocols take into account various parameters, such as current location of a node, node's direction, and the relative positions of source and destination nodes. However, these protocols are incapable of catering for the frequent topological changes in VANETs, yielding recurring network partitions. Moreover, these protocols lack efficient mechanism for traffic load management on a route. Furthermore, the existing protocols do not provide prioritization of safety messages over non-safety messages that adversely impact their performance. To resolve these issues, this paper pioneers the use of two parameters, namely, relative speed among nodes and packet rate, in addition to the existing direction-aware greedy approach for the selection of the best possible route. Relative speed among nodes caters for the frequent topological changes on the network by selecting a route with increased lifetime, whereas packet rate enables efficient traffic load management. Moreover, we propose a novel probabilistic approach for the selection of the best route on the basis of the aforementioned parameters. This work also introduces a new method to prioritize the time-critical safety messages over non-safety messages. Simulation results demonstrate that PDBFS reduces the average packet loss rate by 6.2%, 18.1%, and 23.4% and enhances the average network throughput by 9.3%, 15.3%, and 22.0% in comparison with TDMP, AODV-R, and TDSRP-DC, respectively. Moreover, our proposed PDBFS minimizes average end-to-end delay by 2388 ms, 2914 ms, and 3362 ms and improves the average link lifetime by 3600 ms, 4101 ms, and 4307 ms in comparison with TDMP, AODV-R, and TDSRP-DC, respectively.
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Related topics: Vehicular Ad Hoc Networks (VANETs) · Mobile Ad Hoc Networks · Energy Efficient Wireless Sensor Networks
Thai researcher and institutional participation
Arfat Ahmad Khan · Khon Kaen University
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