Journal ArticleDOI
Link Reliability-Based Adaptive Routing for Multilevel Vehicular Networks
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TLDR
A dynamic link reliability model is established to portray the link complexity of multilevel VANET scenario, and a link reliability-based adaptive routing algorithm (LRAR) is proposed to improve the transmission efficiency.Abstract:
In multilevel vehicular ad-hoc network (VANET) scenario, dynamic vehicles, complex node distribution and poor wireless channel environment deteriorate the reliability of routing protocols. However, for the key issues of relay selection, existing algorithms analyze the wireless link performance without considering the influence of dynamics and shadow fading on location from GPS, as well as channel condition and buffer queue, which would lead to inaccurate link characterization and maladaptive to network variation. In this paper, we establish a dynamic link reliability model to portray the link complexity of multilevel VANET scenario, and propose a link reliability-based adaptive routing algorithm (LRAR) to improve the transmission efficiency. Firstly, we propose a Kalman filter-based estimation approach to amend GPS original data for precise location of vehicles. Then, we define link reliability to quantify the wireless link performance, and establish a multilevel dynamic link model (MDLM) to evaluate it. Moreover, to accurately describe the complexity of wireless links, we integrate the corrected GPS data and characteristics of multilevel VANET including vehicle dynamics, distribution hierarchy and shadow fading into the modeling of link reliability. Considering the difference of link state among diverse vehicles, a maximum deviation algorithm is introduced to adaptively calculate the weight of each parameter in the modeling. Finally, we formulate the routing decision as a multi-attribute decision problem, and select the link with highest reliability as transmission path. Simulation results demonstrate that LRAR outperforms the existing routing algorithms in terms of average end-to-end delay and packet delivery ratio.read more
Citations
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A Multihop Task Offloading Decision Model in MEC-Enabled Internet of Vehicles
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A Multihop Task Offloading Decision Model in MEC-Enabled Internet of Vehicles
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References
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Proceedings ArticleDOI
GPSR: greedy perimeter stateless routing for wireless networks
Brad Karp,Hsiang-Tsung Kung +1 more
TL;DR: Greedy Perimeter Stateless Routing is presented, a novel routing protocol for wireless datagram networks that uses the positions of routers and a packet's destination to make packet forwarding decisions and its scalability on densely deployed wireless networks is demonstrated.
Proceedings ArticleDOI
Enhanced Perimeter Routing for Geographic Forwarding Protocols in Urban Vehicular Scenarios
TL;DR: GpsrJ+ is described, a solution that further improves the packet delivery ratio of GPCR with minimal modification by predicting on which road segment its neighboring junction node will forward packets to and allows geographic routing schemes to return to the greedy mode faster.
Journal ArticleDOI
Vehicular Communications: A Network Layer Perspective
TL;DR: In this paper, the authors provide a comprehensive overview of vehicular communications from the network layer perspective and identify the challenges confronted by the current vehicular networks and present corresponding research opportunities.
Journal ArticleDOI
Maximizing deviation method for neutrosophic multiple attribute decision making with incomplete weight information
Rıdvan źAhin,Peide Liu +1 more
TL;DR: In this paper, a method for solving the multiple attribute decision-making problems with the single-valued neutrosophic information or interval neutralization information was developed, where two discrimination functions referred to as score function and accuracy function were proposed.
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