international journal of informative & futuristic research issn: … · wireless communications...
TRANSCRIPT
8010
This work is published under Attribution-NonCommercial-ShareAlike 4.0 International License
Copyright©IJIFR 2017
International Journal of Informative & Futuristic Research ISSN: 2347-1697
Volume 4 Issue 10 June 2017 www.ijifr.com
Abstract
In the last few years, Vehicular ad hoc networks (VANETs) have been quite a hot research area for the research community. Due to their unique characteristics such as high dynamic topology and predictable mobility, VANETs attract so much attention of both academia and industry. In this research work, an overview of the main aspects of VANETs from an Intelligent Transport Systems (ITS) research perspective is discussed. Research in the field of Intelligent Transport Systems (ITS) is emerging, motivated by the need for improved road safety and environmental concerns. To function properly, these applications require efficient routing protocols. However, existing mobile ad hoc network routing and forwarding approaches have limited performance in VANETs. This paper shows that routing protocols (like LAR and D-LAR) which account for VANET-specific characteristics in their designs, such as high density and
Simulation and modelling the performance
of Vehicular Communication for Intelligent
Transport Systems
Paper ID IJIFR/V4/ E10/ 033 Page No. 8010-8025 Subject Area Computer
Science
Key Words VANET, ITS, Routing Protocol, LAR, D-LAR, SBM method, Naya Raipur,
SUMO, NS-2
1st Neha Patel
M.Tech. Scholar,
Department of Computer Science,
School of Engineering & IT,
MATS University, Raipur-Chhattisgarh,India
2nd Deepak Kumar Xaxa
Assistant Professor,
Department of Computer Science,
School of Engineering & IT,
MATS University, Raipur-Chhattisgarh,India
3rd Devendra Kumar
M.Tech. Scholar,
Department of Computer Science,
School of Engineering & IT,
MATS University, Raipur-Chhattisgarh,India
8011
ISSN: 2347-1697
International Journal of Informative & Futuristic Research (IJIFR)
Volume - 4, Issue -10, June 2017
Continuous 46th Edition, Page No.: 8010-8025
Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::
Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems
constrained mobility can provide good performance for a large spectrum of ITS applications. The main aspect and key concept for VANET simulations are a real world vehicular mobility model which will ensure conclusions drawn from simulation experiments will carry through to real world deployments. In this paper a tool called SUMO that allows users to easily generate real world mobility models for VANET simulations is considered. The real world city map like Naya Raipur cities drown using OpenStreetMap (OSM) which is a map of the real world and free to use under an open license. In experiment phase, intelligent transport system is implemented in Raipur city map and investigated the performance analysis of LAR and D-LAR routing protocol. Output of SUMO simulator is a real world mobility model and can be used by network simulator, NS-2. In this research work a Safety Message Broadcasting method (SBM) is proposed which forwards and notifies the vehicles about their speed and direction. The simulation results are obtained between SBM method, LAR and D-LAR protocol when nodes are moving according to a real world mobility model which is significantly different from that of the generally used random waypoint model at highway scenario. SBM method shows 6.16% in packet delivery ratio, 11.76% improvement in throughput, 6.09% improvement in average delay, 20.63% improvement in routing overhead and 15.74% improvement in normalized routing load as compared to D-LAR protocol.
I. INTRODUCTION
Wireless Communications in vehicular environments are operated by Intelligent
Transport Systems (ITS) for Vehicular Ad-Hoc Networks (VANETs). They are designed
and deployed with a motive to provide a consistent and secure environment for drivers by
cut down road accidents, traffic jams, and fuel consumption and so on. The car drivers
are notified about dangerous conditions by vehicle to vehicle (v-2-v) communications
and exchanging the messages about surrounding environments [1], [2]. The vehicular
networks are the advanced form of Mobile Ad hoc Networks (MANETS) and inherits
most of the characteristics such as high rate of topology change, high mobility , high
number of nodes and so on [1].[3]-[7].
An Intelligent Transport System (ITS) would be the future technology that plays a vital
role in solving real time accident and traffic jam conditions. An ITS is the advanced form
of Vehicular Ad Hoc networks which facilitates it by exchanging information among
vehicles in a precise manner with short dely. Furthermore, due to movement of vehicles
with varying speed in arbitrary direction makes the complexity for designing efficient
routing protocols. So far, Location added Routing (LAR) and its advanced form is
preferred for routing purpose in vehicular environment. Although, research in intelligent
transport systems is going over the world and quite very well implemented in USA and
European counties.
8012
ISSN: 2347-1697
International Journal of Informative & Futuristic Research (IJIFR)
Volume - 4, Issue -10, June 2017
Continuous 46th Edition, Page No.: 8010-8025
Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::
Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems
In this paper, a smart way of broadcasting of message exchange among vehicles is
considered and a new method so called Smart Broadcasting & Modelling (SBM) method
is proposed. The research domain is vehicular ad hoc networks in which the latest trend
of research in Intelligent Transport System is studied. Initially, the proposed work also
studies the some basic routing protocol which is usually opted for routing in VANETs.
The incidence of congestion rises up the delay and packet loss (particularly for safety
messages) leading to alleviation of the VANETs’ routine [8]-[11]. The congestion be
able to be controlled in VANETs in diverse customs such as by modification the
transmission rate, modification the transmission power, shaping the contention window
size and prioritizing and scheduling the messages [13]-[22]. Moreover, congestion
control approaches in VANETs countenance some troubles which involves high
transmission delay, unfair resource usage, inefficient bandwidth usage, communication
overhead, and computing overheads, and so on [10], [13]-[22]. Therefore, a new
method is needed that would consider congestion problem and should be developed a
smart way of broadcasting of message to control delaying of messages that cause
congestion in network, particularly in serious situations where the safety messages be
supposed to be delivered without any significant delay and packet loss.
II. ARCHITECTURE OF VANETS
Figure 1 depicts three district domains of VANETs including In-vehicle domain,
Ad hoc domain, and infrastructure domain. In-vehicle domain is formed of OBUs.
Each vehicle is considered to be equipped with OBU. Short range wireless
communication is generated by OBUs for safety and non-safety communications. The
second domain is Ad hoc domain which is composed of OBUs and RSUs. OBUs
communications can be conducted by one-hop communication or multi-hop
communications that depend on the applications generating these communications
[24], [28]. The third domain is Infrastructure domain that is composed by RSUs and
Hotspots (HS). Infrastructure domain is employed to access the safety and non-safety
applications. RSUs provide internet access, and HS is considered for low
controlled environments. In the case that RSUs or HSs cannot provide internet access,
OBUs can employ integrated cellular networks including General packet radio service
(GPRS), Global System for Mobile Communications (GSM), Universal Mobile
Telecommunications System (UMTS), 4G, and WiMAX [24], [28].
Figure 1: VANET System Architecture [28]
8013
ISSN: 2347-1697
International Journal of Informative & Futuristic Research (IJIFR)
Volume - 4, Issue -10, June 2017
Continuous 46th Edition, Page No.: 8010-8025
Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::
Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems
III. RELATED WORK
Routing has been a major research topic in MANETs. DSDV [30] and DSR [25] are
protocols that focus on the topology of the network to select the end-to-end
communication path. DSDV is a proactive protocol that may work well in small static
environments, but does not scale well in larger, dynamic environments in which link
information are frequently updated. RBVT-P is a proactive kind of routing protocol as
well, but unlike DSDV routing protocol it is not coupled to individual nodes. RBVT-P
creates a real-time outlook of the vehicular traffic on the roads. DSR is a source-based
routing that creates routes on-demand. The RBVT-R settles routes on-demand, but these
two routing protocols vary in the representation of the routes. In DSR routing protocol,
routes are series of nodes, thus leading to regular route break in VANETs, while in
RBVT-R, the routes are sequences of road intersections defining connected road
segments.
To pick up on traditional node-centric routing protocols that do not reflect on the road
topology, a hardly any protocols for VANETs [31, 32] take advantage of the fact that
movements of vehicles are constrained on roads to either predict the lifetime of routes in
node-centric protocols (and repair routes before they break) or reduce the number of
route breaks by selecting, during the route creation, neighbours moving in the same
direction and with a small relative speed. RBVT-R routing protocol vary from these
protocols in that the routes are road-based and their main mechanism are the road
intersections traversed on the path from source to destination.
Geographical routing protocols, such as GPSR [26], GFG [33], and GOAFR [34], use
node positions to route data between end-points. In static ad hoc networks, for which they
have been initially premeditated, they balance well because the only overhead is
generated by “hello” messages to keep informed the neighbour lists. However, under high
mobility VANETs, the recovery strategies proposed in the literature (when a forwarding
node cannot be found) are often based on planar graph traversals, which were shown not
to be as effective in VANETs due to radio obstacles, high node mobility, and the fact that
vehicle movements are constrained on roads, rather than being uniformly distributed
across a region [22].
The main concepts of anchor-based routing in sensor networks [35, 36] have been
adapted to vehicular networks environments. GSR [22] and SAR [37] integrate the road
topologies in routing using those concepts. In these routing protocols, a source node
calculates the shortest road based path from its current position to the destination. Similar
to RBVT, they include the list of intersections that defines the path from source to
destination in the header of each data packet sent by the source node. On the other hand,
[22], [37] do not think upon the real-time vehicular traffic, and as a result, they could
comprise empty roads or roads with network partitions. To alleviate this issue, A-STAR
[38] modifies GSR by giving preference to streets served by transit buses each time a
new intersection is to be added to the source route. The recently introduced CAR [23]
protocol finds connected paths between source and destination pairs considering real-time
8014
ISSN: 2347-1697
International Journal of Informative & Futuristic Research (IJIFR)
Volume - 4, Issue -10, June 2017
Continuous 46th Edition, Page No.: 8010-8025
Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::
Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems
traffic. CAR uses “guards” added to “hello” messages to reflect the movements of the
source and destination nodes on the paths. Gytar [39] does not accumulate the full
intersection-based route in the packets. Instead, the selection of the next intersection is
made dynamically, each time choosing the next road segment with the best balance of
road density and road length.
MDDV [40] and VADD [41] use opportunistic forwarding to transport data from source
node to destination node. VADD uses historic data traffic flow to determine the best
route to the destination. MDDV considers the road traffic conditions as well as the
number of lanes on each road segment to select the best road-based trajectory to forward
data. In both routing protocols, whenever no vehicle node can be established by the
forwarding trajectory, a carry and-forward mechanism is used. The vehicle node which is
unable to transmit the data packet will store it until it finds a more suitable relay. These
protocols are well suited for delay tolerant applications i.e. applications for which the
users can tolerate a certain level of delay (up to a minute or more), as long as the data
eventually arrives. On the other hand, the RBVT routing protocols provide support for
applications that are not delay tolerant. RBVT protocols require that an end to end path
exists for data to reach the destination. Under very sparse vehicular traffic, as well as at
the early stages of the deployment of wireless technology in vehicles (while many
vehicles do not have wireless interfaces), opportunistic forwarding solutions, such as
these, will be needed for car-to-car ad hoc communications.
Note that real-life measurements with commercial GPS receivers [42] showed errors in
reporting of GPS positions in urban environment. Because RBVT protocols follow paths
made of road segments, they are more resilient to vehicle node positions errors of a few
meters. The integration of inertial navigation system to GPS receivers is expected to
improve the detection and handling of GPS position errors.
IV. PROBLEM IDENTIFICATION
The previous research is been discussed with Intelligent Transport System (ITS)
application in regards with vehicular ad hoc networks. As discussed in chapter 1 that ITS
application is future onwards application that would be utilized and ongoing research in
developed countries (like America, France, and Russia etc.). So, safety concern is
discussed to create communication among vehicles without any delay or collision. Also
the routing protocols performance is taken into account for a city traffic scenario.
Location aided routing (LAR) and directional location aided routing (D-LAR) protocols
are compared and simulated. The realistic environment is created by using SUMO
simulator and performance evaluation is done by using network Simulator 2. The
simulation was performed over three hundred vehicles and delay & network parameters
are considered. In the previous study, D-LAR performs better than the LAR protocol for city traffic
environment for VANETs and its enhancement is required. Both of them were compared
protocol on behalf of delay and hop count consideration. The author includes that future
8015
ISSN: 2347-1697
International Journal of Informative & Futuristic Research (IJIFR)
Volume - 4, Issue -10, June 2017
Continuous 46th Edition, Page No.: 8010-8025
Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::
Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems
enhancement of D-LAR protocol is needed and it must be tested for other network
parameters too. As per ITS application is concerned, there could be improvement in a
routing protocol in city traffic environment for VANETs regarding location & speed of
vehicles. Also more parameters should be considered to contribute depth research, so
parameters more could be considered. Network congestion is not taken into consideration
since large scale city environment are characterized by high density of vehicles in
VANETs and their communication exchange may burden the wireless channel with high
traffic loads.
After formulation of problem identification phase, a new approach is proposed in this
paper called Smart Broadcasting and Modelling (SBM) method for vehicular
communication based on hop count analysis in ITS. In this method, a vehicle with status
update to transmit the data first listens to the channel. If the channel is ideal, the packet is
sent and if the channel is busy, the transmission is deferred for a random amount of ideal
channel time and then sent.
The proposed system formulates the VANET-ITS system model in which real world map
considered like city traffic road network (Naya Raipur) traffic environment. This would
help to find the best routes that maximize the Quality of Service (QoS) evaluated in terms
of connectivity, delay and packet delivery ratio. For Smart broadcasting of
communication packets, the proposed system implements broadcast function which
makes adaptive network exploration and integration of communication pairs and updates
the latest routing information along the routes.
V. PROPOSED METHODOLOGY
To support Intelligent Transport System applications, routing protocols of VANETs must
be able to efficiently transmit packets to related destinations. In order to cope with the
challenges described in previous chapter 3, we propose in this paper Digital Signature
based VANET-ITS architecture routing protocol performance analysis which would be
suitable for large-scale real world scenarios . One objective of these routing protocols is
to search the best QoS routing path which satisfies with different ITS applications
requirements based on real-time QoS of road side conditions & constraints expressed in
terms of namely connectivity probability, delay and packet delivery ratio. Besides, these
routing protocols are adaptive and scalable, and can effectively decrease redundant
overhead to cope with network congestion and limited bandwidth in VANETs.
Phase 1: The first objective to implement Safety Broadcasting and Modeling (SBM)
method, it is needed to form an intelligent transport system which is best suitable of
vehicular network architecture. A hypothesis is made that an ITS model would be
simulated using a real world map scenario and for this purpose a location of Naya Raipur
from Chhattisgarh is chosen. Here, the performance of LAR, D-LAR and SBM
mechanism routing performance would be analyzed for their better performance.
Phase 2: To implement SBM method a broadcast function is implemented in appropriate
files for network simulator 2. This function forwards the direction and speed of the
8016
ISSN: 2347-1697
International Journal of Informative & Futuristic Research (IJIFR)
Volume - 4, Issue -10, June 2017
Continuous 46th Edition, Page No.: 8010-8025
Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::
Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems
vehicle. This function is timely broadcasted to other vehicles to be aware of each other
vehicles information about speed and their direction of moving.
Figure 2: SBM Phases
Phase 3: There is a unique method from which a real world map is actually been
simulated. For this purpose, a real world map location like naya Raipur from
Chhattisgarh is chosen in OpenstreetMap, and this map is extracted. Then this extracted
map is imported to Sumo simulator where many vehicles can be visualized and deployed.
In this set of experiment, number of vehicles ranges from 100 to 300 vehicles. Since the
primary objective of experiment is the analysis of routing protocols, so the traces of sumo
simulator is imported to network simulator 2 as mobility files for getting vehicles
movement.
Phase 4: In this phase, three routing protocols namely LAR, D-LAR and SBM are
analyzed and compared their routing performance when they are taken into consideration
for real world map scenario for naya Raipur from Chhattisgarh.
Phase 5: In the final phase, results obtained for routing protocols are plotted into a graph
to visualize the performance of LAR, D-LAR and SBM Mechanism. At this phase, it is
easily conclude that how much percentage improvement showed the SMB mechanism
over LAR and D-LAR method.
When a simulation scenario for an intelligent transport system for vehicular ad hoc
network is ready then vehicles need to broadcast a hello message for their status about
8017
ISSN: 2347-1697
International Journal of Informative & Futuristic Research (IJIFR)
Volume - 4, Issue -10, June 2017
Continuous 46th Edition, Page No.: 8010-8025
Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::
Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems
their location. This process updates the routing table for the routing protocol. A source
vehicle node sends a data packet to the nearby neighbour vehicle about the status and
direction of moving using Smart Broadcasting and Modelling (SBM) method. This
method forwards the location and direction of vehicle as well as the speed of the vehicle
to neighbour vehicles for safety purpose so that no other vehicle comes with that lane on
which the source vehicle moving. The neighbour vehicles after receiving safety message,
forwards this message to other vehicles of the network for safety. If the safety message is
received successfully, they forward it and continue communication and finally a reply
function is invoked to reply the source vehicle that, a lane is clear to move forward and
safety messages is successfully delivered to the network. If the neighbour vehicles fail to
forward the safety message, it tries once to re-transmit the safety message, and then stop
the communication.
Figure 3: SBM Flowchart
8018
ISSN: 2347-1697
International Journal of Informative & Futuristic Research (IJIFR)
Volume - 4, Issue -10, June 2017
Continuous 46th Edition, Page No.: 8010-8025
Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::
Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems
VI. RESULTS AND GRAPHS
In this paper, Naya Raipur city map is considered, instead of considering any random
map or grid map. Considered real map has been taken and processed using
OpenStreetMap (OSM). The map processing consists of embedding real time
environmental events like traffic on road and traffic signals. This processed map is
visualized using SUMO simulator GUI. Figure 4 shows extracted Naya Raipur City Map
in SUMO for VANET-ITS simulation. Figure 5 shows the view of Naya Raipur City
Map in a Sumo Simulator where the road side structure of a city traffic scenario could be
seen. Figure 5 shows the vehicles movements in a road structure obtained in SUMO
simulator. In this figure all the vehicles are moving with their ids shown. The vehicles are
deployed from 100 vehicles to 300 vehicles using SUMO simulator.
Figure 4: Snapshot of Naya Raipur City Map
Figure 5: SUMO view of Naya Raipur
8019
ISSN: 2347-1697
International Journal of Informative & Futuristic Research (IJIFR)
Volume - 4, Issue -10, June 2017
Continuous 46th Edition, Page No.: 8010-8025
Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::
Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems
Figure 6 (a) shows the graph of throughput.
Figure 6: (a) Throughput
The Graph clearly shows that throughput is higher, in case of SBM method with Naya
Raipur highway scenario. It is increasing for all number of vehicles because the no. of
packets to be sent over the network is dropping over larger networks for all scenarios.
While in case of LAR and D-LAR protocol with Raipur highway scenario there is little
decrease in the throughput because the no. of vehicles are less managed over larger
network ranging from 100 to 300 vehicular nodes. The SBM method showed 11.76%
improvement than D-LAR routing protocol.
Figure 6 (b) shows the graph of Packet Delivery Ratio. The Graph clearly shows a
decrease in percentage of packet delivery ratio in case of both LAR and D-LAR routing
protocols.
Figure 6: (b) Packet Delivery Ratio
8020
ISSN: 2347-1697
International Journal of Informative & Futuristic Research (IJIFR)
Volume - 4, Issue -10, June 2017
Continuous 46th Edition, Page No.: 8010-8025
Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::
Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems
It is sharply decreased after 100 nodes because the no. of nodes increased over the
network and there is much more nodes are sent with RREQ messages to find the required
destination node as the route is captured due to congestion in the network. Hence, graph
shows that SBM method performs well under all scenarios compared to LAR and D-LAR
protocols. The SBM method showed 6.16% improvement than D-LAR routing protocol.
Figure 6 (c) shows the graph of End to End Delay.
Figure 6: (c) End to End Delay
The Graph clearly shows an increase in percentage of end to end delay in case of both
LAR and D-LAR routing protocols. It is increasing because the no. of packets has to send
over the network which is increasing the no. of vehicle nodes with next to next scenario.
Hence, LAR and D-LAR not performs well under urban scenario larger network
compared to SBM method under NAYA RAIPUR City urban scenario. Therefore, End to
End Delay graph shows that LAR and D-LAR protocol is much more affected as there is
very big difference in the output for all scenarios than SBM method based routing
protocol. The SBM method showed 6.09% improvement than D-LAR routing protocol.
Figure 6 (d) shows the graph of Normalized Routing Load.
Figure 6: (d) Normalized Routing Load
8021
ISSN: 2347-1697
International Journal of Informative & Futuristic Research (IJIFR)
Volume - 4, Issue -10, June 2017
Continuous 46th Edition, Page No.: 8010-8025
Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::
Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems
The Graph clearly shows that delay is quite similar in all cases i.e. LAR, D-LAR and
SBM method up to 300 nodes. This is due to the nature of internal performance of
routing protocols that it gives the fake reply to the neighbour’s vehicles that it is the part
of the network. There is increase in the NRL after 100 nodes because the no. of vehicles
nodes increases in the topology from 100 to 300. Therefore, NRL graph shows that both
protocols are little affected as there is small difference in the output for all scenarios. The
SBM method showed 15.74% improvement than D-LAR routing protocol.
Figure 6 (e) shows the routing overhead for SBM method, LAR and D-LAR protocols.
The graph shows the gradually increase in routing overhead since the number of route
request and route send packets increase as the number of vehicles increase to
communicate with each other. Overall, SBM method has lower routing overhead than
LAR and D-LAR routing protocols.
Figure 6 (e): Routing Overhead
This chapter outlined performance constraints and metrics for the SBM, LAR and D-
LAR protocols being investigated in this study. The set of experiments are then
introduced and the relative performance of the protocols under each usage scenario is
explained. This chapter provided a comparison of the performance of each protocol under
different traffic loads. The results of the comparisons have highlighted the best
performance of SBM method than LAR and D-LAR protocol for all scenarios. The SBM
method showed 20.63% improvement than D-LAR routing protocol.
VII. CONCLUSION AND FUTURE WORK
After formulation of problem identification phase, a new approach is proposed in this
paper called Smart Broadcasting and Modelling (SBM) method for vehicular
communication based on hop count analysis in ITS. In this method, a vehicle with status
update to transmit the data first listens to the channel. If the channel is ideal, the packet is
sent and if the channel is busy, the transmission is deferred for a random amount of ideal
channel time and then sent. The proposed system formulates the VANET-ITS system
8022
ISSN: 2347-1697
International Journal of Informative & Futuristic Research (IJIFR)
Volume - 4, Issue -10, June 2017
Continuous 46th Edition, Page No.: 8010-8025
Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::
Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems
model in which real world map considered like city traffic road network (Naya Raipur)
traffic environment. This would help to find the best routes that maximize the Quality of
Service (QoS) evaluated in terms of connectivity, delay and packet delivery ratio. For
Smart broadcasting of communication packets, the proposed system implements
broadcast function which makes adaptive network exploration and integration of
communication pairs and updates the latest routing information along the routes.
To simulate real world map traffic scenario, the proposed method uses the
OpenStreetMap to choose the metro city environment. This trace is then imported to
SUMO simulator and then the performance f routing protocols is tested in Network
Simulator 2. The SBM method is compared with D-LAR and LAR protocols to evaluate
the routing performance by considering related traffic information, vehicle distribution,
communication range, channel transmission rate, road length and so on. The parameters
for performance considered are: End to End Delay, Packet Delivery Ratio, Packet Loss
Ratio, NRL and Throughput.
There is considerable concern regarding reliability of messages and subsequent
evaluation for revocation. So this work can be further extended for checking reliability of
messages as well as design of parameters for an efficient certificate revocation procedure
in a VANET based Intelligent Transport Systems. Furthermore bigger and more complex
topologies are on the way in order to cover more realistic VANET scenarios. Further plan
is going to investigate more Position-based Algorithms and implement into NS-2 as well
as to testing into realistic VANET scenarios.
VIII. REFERENCES
[1] K. Golestan, A. Jundi, L. Nassar, F. Sattar, F. Karray, M. Kamel, et al., "Vehicular ad-hoc
networks (VANETs): capabilities, challenges in information gathering and data fusion,"
Autonomous and Intelligent Systems, ed: Springer, pp. 34-41, 2012.
[2] G. Karagiannis, O. Altintas, E. Ekici, G. Heijenk, B. Jarupan, K. Lin, et al., "Vehicular
networking: A survey and tutorial on requirements, architectures, challenges,
standards and solutions," IEEE Communications Surveys & Tutorials, vol. 13, pp. 584-
616, 2011.
[3] J. Guerrero-Ibáñez, C. Flores-Cortés, and S. Zeadally, "Vehicular Ad-hoc Networks
(VANETs): Architecture, Protocols and Applications," Next-Generation Wireless
Technologies, ed: Springer, pp. 49-70, 2013.
[4] S. Zeadally, R. Hunt, Y.-S. Chen, A. Irwin, and A. Hassan, "Vehicular ad hoc networks
(VANETS): status, results, and challenges," Telecommunication Systems, vol. 50,
pp. 217-241, 2012.
[5] Y. Qian and N. Moayeri, "Design of secure and application-oriented VANETs,"
Vehicular Technology Conference, 2008. VTC Spring 2008. IEEE, 2008, pp. 2794-2799.
[6] Y. Liu, F. Dion, and S. Biswas, "Dedicated short-range wireless communications
for intelligent transportation system applications: State of the art," Transportation
Research Record: Journal of the Transportation Research Board, pp. 29-37, 2005.
[7] M. R. J. Sattari, R. M. Noor, and S. Ghahremani, "Dynamic congestion control algorithm
for vehicular ad hoc networks," International Journal of Software Engineering and
Its Applications, vol. 7, pp. 95-108, 2013.
8023
ISSN: 2347-1697
International Journal of Informative & Futuristic Research (IJIFR)
Volume - 4, Issue -10, June 2017
Continuous 46th Edition, Page No.: 8010-8025
Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::
Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems
[8] T. Ghosh and S. Mitra, "Congestion control by dynamic sharing of bandwidth
among vehicles in VANET," Intelligent Systems Design and Applications (ISDA),
2012 12th International Conference on, pp. 291-296, 2012.
[9] M. Jabbarpour Sattari and R. Md Noor, "Dynamic D-FPAV congestion control for
algorithm for VANETs to rescue human lives," Archives Des Science, vol. 65, 2012.
[10] M. Sepulcre, J. Mittag, P. Santi, H. Hartenstein, and J. Gozalvez, "Congestion and
awareness control in cooperative vehicular systems," Proceedings of the IEEE, vol. 99,
pp. 1260-1279, 2011.
[11] R. K. Singh and N. Tyagi, "Challenges of Routing In Vehicular Ad Hoc
Networks: A Survey," IJECCE, vol. 3, pp. 126-132, 2012.
[12] N. Taherkhani and S. Pierre, "Congestion control in vehicular ad hoc networks
using Meta-heuristic techniques," Proceedings of the second ACM international
symposium on Design and analysis of intelligent vehicular networks and applications, pp.
47-54, 2012.
[13] X. Shen, X. Cheng, R. Zhang, B. Jiao, and Y. Yang, "Distributed congestion
control approaches for the IEEE 802.11 p vehicular networks," IEEE Intelligent
Transportation Systems Magazine, vol. 5, pp. 50-61, 2013.
[14] M. Torrent-Moreno, J. Mittag, P. Santi, and H. Hartenstein, "Vehicle-to-vehicle
communication: fair transmit power control for safety-critical information," IEEE
Transactions on Vehicular Technology, vol. 58, pp. 3684-3703, 2009.
[15] M. Sepulcre, J. Gozalvez, J. Härri, and H. Hartenstein, "Contextual communications
congestion control for cooperative vehicular networks," IEEE Transactions on Wireless
Communications, vol. 10, pp. 385-389, 2011.
[16] IEEE Std. 802.11p/D8.0, IEEE Draft Standard for Wireless LAN Medium Access Control
(MAC) and Physical Layer (PHY) Specifications, IEEE, Piscataway, N.J., 2009.
[17] D. B. Rawat, D. C. Popescu, G. Yan, and S. Olariu, "Enhancing VANET performance by
joint adaptation of transmission power and contention window size," IEEE Transactions
on Parallel and Distributed Systems, vol. 22, pp. 1528-1535, 2011.
[18] M. Torrent-Moreno, D. Jiang, and H. Hartenstein, "Broadcast reception rates and effects
of priority access in 802.11-based vehicular ad-hoc networks," Proceedings of the
1st ACM international workshop on Vehicular ad hoc networks, pp. 10-18, 2004.
[19] H. Hartenstein and K. Laberteaux, "VANET vehicular applications and inter-networking
technologies," vol. 1: John Wiley & Sons, 2009.
[20] M. S. Bouassida and M. Shawky, "On the congestion control within VANET," Wireless
Days, 2008. WD'08. 1st IFIP, pp. 1-5, 2008.
[21] S. Bai, J. Oh, and J.-i. Jung, "Context awareness beacon scheduling scheme for
congestion control in vehicle to vehicle safety communication," Ad Hoc Networks, vol.
11, pp. 2049-2058, 2013.
[22] M. S. Bouassida and M. Shawky, "A cooperative congestion control approach
within VANETs: formal verification and performance evaluation," EURASIP Journal
on Wireless Communications and Networking, vol. 2010, no. 11, 2010.
[23] L. Nassar, A. Jundi, K. Golestan, F. Sattar, F. Karray, M. Kamel, et al., "Vehicular ad-hoc
Networks (VANETs): capabilities, challenges in context-aware processing and
communication gateway," Autonomous and Intelligent Systems, ed: Springer, pp. 42-49,
2012.
[24] M. Kaur, "Vehicular ad hoc networks," Journal of Global Research in Computer Science,
vol. 3, pp. 61-64, 2012.
[25] N. Gul, N. Qamar, and A. Shahzad, "A Survey on Architecture, Protocols, Challenges and
Solutions on Vehicular Networking." T. ETSI, "102 638 Intelligent Transport Systems
8024
ISSN: 2347-1697
International Journal of Informative & Futuristic Research (IJIFR)
Volume - 4, Issue -10, June 2017
Continuous 46th Edition, Page No.: 8010-8025
Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::
Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems
(ITS); Vehicular Communications; Basic Set of Applications; Definitions," ETSI, Sophia
Antipolis Cedex, France, 2009.
[26] M. L. Sichitiu and M. Kihl, "Inter-vehicle communication systems: a survey,"
Communications Surveys & Tutorials, IEEE, vol. 10, pp. 88-105, 2008.
[27] A. Festag, G. Noecker, M. Strassberger, A. Lübke, B. Bochow, M. Torrent-
Moreno, et al., "’NoW–Network on Wheels’: Project objectives, technology and
achievements," 2008.
[28] Y. Gui and E. Chan, "Data Scheduling for Multi-item Requests in Vehicle-Roadside Data
Access with Motion Prediction Based Workload Transfer," 26th International Conference
on Advanced Information Networking and Applications Workshops (WAINA), pp. 569-
574, 2012.
[29] C. Campolo, A. Vinel, A. Molinaro, and Y. Koucheryavy, "Modeling broadcasting
in IEEE 802.11 p/WAVE vehicular networks," IEEE Communications Letters, vol. 15,
pp. 199-201, 2011.
[30] Y. Zhang, L. Yang, H. Liu, and L. Wu, "A channel coordination scheme for high density
vehicular ad-hoc networks based on time division multiplexing," Journal of
Communications, vol. 9, 2014.
[31] A. K. K. Aboobaker, "Performance analysis of authentication protocols in vehicular
ad hoc networks (VANET)," Master of Science Thesis, Department of Mathematics,
University of London, September, vol. 2, 2010.
[32] M. Khatri, "An insight overview of issues and challenges in vehicular adhoc network,"
Journal of Global Research in Computer Science, vol. 2, pp. 47-50, 2012.
[33] A. S. Tanenbaum, "Computer networks, 5-th edition," ed: Prentice Hall, 2011.
[34] B. Subramani and E. Chandra, "A survey on congestion control," Global Journal of
Computer Science and Technology, vol. 9, 2010.
[35] J. Widmer, R. Denda, and M. Mauve, "A survey on TCP-friendly congestion
control," IEEE Network, vol. 15, pp. 28-37, 2001.
[36] J. F. Kurose, Computer Networking: A Top-Down Approach Featuring the Internet, 3/E:
Pearson Education India, 2005.
[37] C. Casetti, M. Gerla, S. Mascolo, M. Y. Sanadidi, and R. Wang, "TCP Westwood: end-
toend congestion control for wired/wireless networks," Wireless Networks, vol. 8, pp.
467-479, 2002.
[38] M. Gerla, M. Y. Sanadidi, R. Wang, A. Zanella, C. Casetti, and S. Mascolo, "TCP
Westwood: Congestion window control using bandwidth estimation," IEEE Global
Telecommunications Conference, 2001. GLOBECOM'01., pp. 1698-1702, 2001.
[39] C. Lochert, B. Scheuermann, and M. Mauve, "A survey on congestion control for mobile
ad hoc networks," Wireless Communications and Mobile Computing, vol. 7, pp. 655-676,
2007.
[40] G. T. Nguyen, R. H. Katz, B. Noble, and M. Satyanarayanan, "A trace-based approach for
modeling wireless channel behavior," Proceedings of the 28th conference on Winter
simulation, 1996, pp. 597-604.
[41] Y. Zang, L. Stibor, X. Cheng, H.-J. Reumerman, A. Paruzel, and A. Barroso, "Congestion
control in wireless networks for vehicular safety applications," Proceedings of the
8th European Wireless Conference, 2007.
[42] M. R. J. Sattari, R. M. Noor, and H. Keshavarz, "A taxonomy for congestion
control algorithms in Vehicular Ad Hoc Networks," IEEE International Conference
on Communication, Networks and Satellite (ComNetSat), , pp. 44-49, 2012.
8025
ISSN: 2347-1697
International Journal of Informative & Futuristic Research (IJIFR)
Volume - 4, Issue -10, June 2017
Continuous 46th Edition, Page No.: 8010-8025
Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::
Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems
PAPER CITATION
Patel, N., Xaxa, K.D., Kumar, D. ( (2017) :: “Simulation and modelling the
performance of Vehicular Communication for Intelligent Transport Systems” International Journal of Informative & Futuristic Research (ISSN: 2347-1697),
Vol. (4) No. (10), June 2017, pp. 8010-8025, Paper ID: IJIFR/V4/E10/033.
Available online through- http://www.ijifr.com/searchjournal.aspx