Inter Vehicle Distance Based Connectivity Aware Routing in Vehicular Adhoc Networks

Hassan, Ahmed Nazar; Kaiwartya, Omprakash; Abdullah, Abdul Hanan; Sheet, Dalya Khalid; Raw, Ram Shringar

doi:10.1007/s11277-017-4831-x

Cited by 34 publications

(10 citation statements)

References 34 publications

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“…In Reference [12], inter vehicle distance is analyzed within connectivity aware routing design for data dissemination. Additionally, in Reference [13], a channel selection framework for location-oriented services in VANET is proposed. However, the performance evaluation of these protocols does not take into account network capacity.…”

Section: Related Workmentioning

confidence: 99%

Transmission Capacity Characterization in VANETs with Enhanced Distributed Channel Access

Liu

Huang

et al. 2019

Electronics

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The traditional research on the capacity of the Vehicular Ad Hoc Networks (VANETs) mainly lacks realistic models mimicking the behaviors of vehicles and the MAC protocol applied by IEEE 802.11p. To overcome these drawbacks, in this paper, the network transmission capacity analysis for VANETs is carried out from the perspective of the spatial geometric relationship among different vehicles. Specifically, the transmission scheme in this system is set to mimic enhanced distributed channel access (EDCA) protocol, in which the division of priorities is taken into account both the data type and the transmission distance requirement. Meanwhile, the moving pattern of vehicles is described as the classic car-following model according to realistic characteristics of VANET, and the propagation channel is modeled as a combination of large-scale path-loss and small-scale Rayleigh fading. Based on this model, the transmission opportunity under EDCA protocol is quantified and compared with that of CSMA/CA, and then the outage probability is calculated under the worst interfered scenario. Finally, the transmission capacity is thereby calculated and verified by the simulation results.

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Section: Related Workmentioning

confidence: 99%

Transmission Capacity Characterization in VANETs with Enhanced Distributed Channel Access

Liu

Huang

et al. 2019

Electronics

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“…Due to problem of connectivity in vehicular network, various parameters such as speed, density, direction and intervehicular distance for measurement of connectivity have been discussed in [8].…”

Section: Related Workmentioning

confidence: 99%

“…Where w 1 and w 2 are the weights we can assign, but keep in mind that w 1 +w 2 = 1, for example w 1 = 0.8, then w 2 = 0.2 If w 2 = 0, and w 1 = 1, it means you are totally ignoring g(n) and f(n), then equation will look like following ( ) ------- (8) VIII. OTHER APPLICATIONS Apart from above discussed technique for specialized purpose, we can also modify this technique for following purposes, like 1) Entertainment Purpose: A song in one vehicle listens by another person in vehicle.…”

Section: Logic Behind Heuristic Functionmentioning

confidence: 99%

IRPanet: Intelligent Routing Protocol in VANET for Dynamic Route Optimization

Ullah¹,

Shah²,

Jilani³

et al. 2019

IJACSA

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This paper presents novel routing protocol, IRPANET (Intelligent Routing Protocol in VANET) for Vehicular Adhoc Network (VANET). Vehicular Ad Hoc Networks are special class of Mobile Adhoc Network, created by road vehicles installed with wireless gadgets). Since the environment is dynamic due to high mobility and the topology changes are too frequent, no connection or path can be established between nodes. The issues are challenging for the design of an effective and efficient protocol for such a dynamic environment. This problem can be solved using probabilistic, heuristic and even machine learning based approaches incorporated with store and forward mechanism. Here, we proposed a design framework using heuristics and probabilistic approaches composite with the time series techniques for selecting best and optimize path for forwarding packets using open street map (OSM). Our proposed algorithm uses various parameters (Heuristics Based Routing) for calculating optimal path for packets to be sent, such geographical position (GPS installed in every vehicle), velocity / speed of vehicle, priority of the packets, distances (Euclidean, Haversine, Vicinity) between vehicle, direction of vehicle, communication range of the vehicle, free buffer of nodes and network congestion. These networks can be used for medical emergency, security, entertainment and routing purposes (applications of VANET). These parameters while used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets especially in medical emergency situation.

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“…Wireless sensor networks (WSNs) have numerous real-life applications in various fields, such as precision agriculture [1], patient healthcare [2], target tracking, homeland security, environmental monitoring, surveillance [3], vehicular traffic management [4,5], and electric vehicle charging recommendation [6,7]. WSNs' role is significant in the emergence of the Internet of Things (IoT) [8,9].…”

Section: Introductionmentioning

confidence: 99%

Enabling Green Wireless Sensor Networks: Energy Efficient T-MAC Using Markov Chain Based Optimization

Ram

Kumar

et al. 2019

Electronics

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Due to the rapidly growing sensor-enabled connected world around us, with the continuously decreasing size of sensors from smaller to tiny, energy efficiency in wireless sensor networks has drawn ample consideration in both academia as well as in industries’ R&D. The literature of energy efficiency in wireless sensor networks (WSNs) is focused on the three layers of wireless communication, namely the physical, Medium Access Control (MAC) and network layers. Physical layer-centric energy efficiency techniques have limited capabilities due to hardware designs and size considerations. Network layer-centric energy efficiency approaches have been constrained, in view of network dynamics and available network infrastructures. However, energy efficiency at the MAC layer requires a traffic cooperative transmission control. In this context, this paper presents a one-dimensional discrete-time Markov chain analytical model of the Timeout Medium Access Control (T-MAC) protocol. Specifically, an analytical model is derived for T-MAC focusing on an analysis of service delay, throughput, energy consumption and power efficiency under unsaturated traffic conditions. The service delay model calculates the average service delay using the adaptive sleep wakeup schedules. The component models include a queuing theory-based throughput analysis model, a cycle probability-based analytical model for computing the probabilities of a successful transmission, collision, and the idle state of a sensor, as well as an energy consumption model for the sensor’s life cycle. A fair performance assessment of the proposed T-MAC analytical model attests to the energy efficiency of the model when compared to that of state-of-the-art techniques, in terms of better power saving, a higher throughput and a lower energy consumption under various traffic loads.

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Inter Vehicle Distance Based Connectivity Aware Routing in Vehicular Adhoc Networks

Cited by 34 publications

References 34 publications

Transmission Capacity Characterization in VANETs with Enhanced Distributed Channel Access

Transmission Capacity Characterization in VANETs with Enhanced Distributed Channel Access

IRPanet: Intelligent Routing Protocol in VANET for Dynamic Route Optimization

Enabling Green Wireless Sensor Networks: Energy Efficient T-MAC Using Markov Chain Based Optimization

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