Improve QoS of IEEE 802.11p Using Average Connected Coverage and Adaptive Transmission Power Scheme for VANET Applications

Improve QoS of IEEE 802.11p Using Average Connected Coverage and Adaptive Transmission Power... It is very challenging task to achieve good Quality of Services (QoS) in highly dynamic topology of Vehicular Ad hoc NETwork (VANET). The Average Connected Coverage (ACC) is very important QoS of VANET to spread emergency information. This paper proposes Connected_Cover algorithm to analyze ACC of VANET using Genetic Algorithm Multi Objective optimization (gamultiobj) tool. Gamultiobj tool generates Pareto front in MATLAB. Using Pareto fronts this paper select transmission range $$TR_{sel}$$ T R s e l and Vehicle density $$Vd_{sel}$$ V d s e l having ACC $$\ge$$ ≥ 95%. This $$Vd_{sel}$$ V d s e l must have ACC $$\ge$$ ≥ 98% when transmission range is 1000 m. Further, the $$TR_{sel}$$ T R s e l and $$Vd_{sel}$$ V d s e l is used in proposed Adaptive Transmission Power (ATP) scheme to improve QoS of VANET. Adaptive transmission power scheme for transmission range 400 and 250 m enhanced the Packet Delivery Fraction (PDF), increased the throughput, decreased the per hop End-to-End Transmission Delay (EETxD) and reduced the retransmissions as compared to Fixed Transmission Power schemes for VANETs safety and warning applications. This paper achieved the PDF and throughput with 250 m ATP scheme higher than 400 m Fixed Power (FP) scheme; also PDF and throughput with 400 m ATP scheme similar to 1000 m FP and ATP scheme for lesser number of nodes (10–50 nodes). The scope of this paper also discusses the number of Road Side Unit (RSU) required in VANET to reduce the cost of system on the basis of ACC. Performance of the system is analyzed using NS-2.35 simulator. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Wireless Personal Communications Springer Journals

Improve QoS of IEEE 802.11p Using Average Connected Coverage and Adaptive Transmission Power Scheme for VANET Applications

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Publisher
Springer US
Copyright
Copyright © 2017 by Springer Science+Business Media New York
Subject
Engineering; Communications Engineering, Networks; Signal,Image and Speech Processing; Computer Communication Networks
ISSN
0929-6212
eISSN
1572-834X
D.O.I.
10.1007/s11277-017-4028-3
Publisher site
See Article on Publisher Site

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