Mobility-Aware GPCR-MA for Vehicular Ad hoc Routing Protocol for Highways Scenario

Mobility-Aware GPCR-MA for Vehicular Ad hoc Routing Protocol for Highways Scenario

Naziya Hussain (SOC, IPS Academy Indore, Indore, India), Priti Maheshwary (Rabindranath Tagore University (Formerly AISECT University), Bhopal, India), Piyush Kumar Shukla (DoCSE, UIT, RGPV, Bhopal, India) and Anoop Singh (CMCC, Mhow, India)
DOI: 10.4018/IJOCI.2018100103
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Vehicular ad hoc network systems are highly important experiments because of enthusiastically exchanging information and symmetric relations of systems. The best transmitting device supports a successful arrangement of networks. This article presents GPCR-MA mobility aware routing protocol concepts based on the Gauss Markov Mobility and Freeway Model. This concept is applied on highway networks because highways have a number of road segment and junctions. The performance of this experiment is verified based on the QoS parameter performance between of the mobility model, which is presented based on their mathematical modeling and simulation structure. After comparing the mobility model based on the parameters: network delay, energy consumption, average throughput and packet delivery ratio, a Freeway mobility model is better in terms of network delay and packet delivery ratio and Gauss Markov model, is better in terms of throughput because it works on broken links in the network, based on rapidly changes in simulation time and increased network traffic length.
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VANET is developed network based on the mobile ad-hoc network specially appointed system, which has provided communications between vehicles to vehicles (V2V) and vehicles to infrastructure (V2I).The particular electronic device will give vehicular network organize availability to the passenger inside vehicles. By these devices working with system does not require a complicate connection between clients to servers and V2V/V2Icommunication.Each and Every vehicle node are well-appointed with Vehicular Network device in the network, which will transmit and receive messages to each other, or we can say these vehicles node will transfer the information to each other inside the network boundary.

The most essential characteristics of a mobility show is the level of authenticity as for the development of users, with all mobility parameters are considered during results analysis. Also, in the fact that there exists no single, comprehensive, mobility model the erroneous determination of an inappropriate model, not emulating the development designs expected in the real-life system condition under consideration of simulation of mobility model for observation and results (Bai, Sadagopan, & Helmy, 2003).

Clearly, engineers and research must assess the effect of their protocols on arranging characteristics and analyze the practices of the network under proposed conditions. Simulation of wireless networks utilizes a few parameters basic to the precision of the simulations at one of the most important amongst the most imperative being the decision of mobility model, which makes the development examples of VANET nodes that structures the differing topology of the network. A typical mobility model initially puts the vehicles node in their underlying areas and characterizes that vehicles node move inside the network Vehicular. Indeed, the mobility model follows the genuine user development through the incorporation of the basic development factors, for example, movement factors, speed, destination, and development histories of the same, or comparative, clients having energy saving for parking vehicle (Bai et al., 2002; Camp, Boleng & Davies, 2002); Lam, Cox, & Widom 2002; Sun, Yu, Liao & Change, 2018). Further, we can work on security and privacy policy on the VANET network with the reference (Wahid et al., 2017; Vijayakumar, Chang, Deborah, Balusamy, & Shynu, 2018).

After study of various research papers and their mathematical modeling and performance metric states that mobility model is affected the network performances, we also illustrate the changes between the mobility model and their mathematical modeling, performance metric based on VANET Ad-hoc routing can be considered based on real time scenario and location-based Ad-hoc routing protocols. The location-based routing protocols, based on the location services for VANET Ad-hoc routing nodes and their geographic positions based on the network simulation. We Consider three VANET Ad-hoc routing protocols to be compared: 1). Greedy Perimeter Coordinator Routing (GPCR) (Markoulidakis, Lyberopoulos, Tsirkas, & Sykas, 1997; Jaap, Bechler, & Wolf, 2005; Kumar & Dave, 2011; Ryu, Cha, Koh, Kang, & Cho, 2011; Hussain, Maheshwary, Shukla, & Singh, 2017). 2).Modified GPCR based on Mobility Awareness GPCR-MA (Hussain et al., 2017; Hussain et al., 2017) in our previous paper and 3).Greedy Perimeter Stateless Routing (GPSR)(Lee, Lee, & Gerla, 2010; Lee, Härri, Lee, & Gerla, 2007; Ning, Jung, Jin, & Kim, 2009), which discover routes through node to node (vehicle to vehicle) with all possible destinations.

The involvement of this paper is used for evaluation of the performance metric of Gauss Markov and Freeway Mobility model on VANET network based on their performance parameter which is used in the model mobility mention in the tabular form, all these performance metric is measured based on the GPCR-MA, GPSR and GPCR Vehicular Ad-Hoc routing protocol.

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