Enhancing AODV routing protocol using mobility parameters in VANET 任課教授:許子衡 教授

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Enhancing AODV routing
protocol using mobility
parameters in VANET
任課教授:許子衡 教授
學生:王志嘉
Introduction

Vehicular Ad-Hoc Networks (VANETs) are special type
of Mobile ad Hoc Networks (MANETs).

Direct wireless transmission from vehicle to vehicle make
it possible to communicate even where there is no
telecommunication infrastructure
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Introduction

The USDOT and IEEE have taken up the standardization
of the associated radio technology Wireless Access for
Vehicular Environments (WAVE),now described as IEEE
802.11p.

There are many challenges in VANETs. According to
FCC frequency allocation we can categorize two main
classes of applications for vehicular ad hoc networks.
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Introduction

The first category which was mentioned above is to
improve the safety level in roads, and the second
predicted to grow very fast in the near future, is
commercial services.

There are many routing protocols for ad hoc networks.
One of the most important of them is AODV. AODV is an
on demand routing protocol. This protocol finds routes
for a node only when it has data packet for transmission.
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Introduction

AODV routing consists of three phases: route discovery,
data transmission and route maintenance.

Route discovery phase starts when a node wants to
transmit data and has no route to destination. Now,
AODV call route discovery process.
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Introduction

In this phase,source node broadcasts a Route Request
Packet(RREQ) to its neighbor.

Nodes that receive RREQ packets divide into three
categories: the receiver node is the destination of route,
the node that has a route to destination or none of both.
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Introduction



After routing phase, routing process calls data
transmission phase, then it transmits data packets across
selected route.
In this phase, it is possible that a link is broken and results
in route expiration.
In this situation, the maintenance phase calls to repair
broken route or find a new route to destination.
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Introduction

One advantage of AODV is that for any pair of source
and destination finds more than one route.

Although this appears as advantage but more often this
advantage acts as disadvantage.

Finding several route need to exchange more control
packet. This leads to increase routing overhead.
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Mobility model



We want improve AODV as MANET routing protocol
and make it useable for VANET with high performance.
We must use one of VANET’s mobility models.
Manhattan is one of the most important mobility models
for VANET.
In Manhattan mobility model, several horizontal and
vertical streets co-exist in the simulation field and mobile
nodes are moving on the lanes of the streets.
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Mobility model

In figure 1, Manhattan has a vertical and a horizontal
street with an intersection. Each street has two directions
be made of a lane.
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Mobility model

If one direction of a lane has positive value 1, then the
lane on the opposite direction must have the negative
value -1.

Streets of each map have the maximum and minimum
allowed velocity (Vmin, Vmax).
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Mobility model



In this mobility model, acceleration is an input parameter.
To calculate node’s next speed, model uses acceleration
and current speed of node, relation 1 shows it:
If β be less than zero, it means that the node is moving
with de-acceleration (negative acceleration) Otherwise,it
moves with positive acceleration.
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Mobility model

If current speed of node is greater than the maximum
allowed velocity for its lane, current speed decreases to
Vmax. Otherwise, if current speed of nodeis less than
minimum allowed velocity for its lane, current speed
increases to Vmin.
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Method description

In our method, we use node’s direction as most important
parameter for next hop selection.

Another parameter, which affects next hop selection, is
node’s position, but importance of this parameter is less
than direction.

These mobility parameters have been obtained from GPS.
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Method description

When a source node wants to send a packet to destination
node, first, routing protocol gets direction of source node
and destination node.

Then, with respect to direction of source node and
destination node, recognize intermediate node that can be
participate in route between source and destination.
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Method description




Because of using Manhattan mobility model, nodes can
move in three situations:
1- Source node and destination node move in same
direction.
2- Source node and destination node move in opposite
direction.
3- Source node and destination are orthogonal.
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Method description

In this paper we have only considered two first situations
and have prolonged it to our future efforts.

In supposed method, we also try to select intermediate
nodes that are moving in suitable position between source
and destination. Furthermore, their direction is important.
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Method description



Corresponding pervious description, a node can be select
as next hop in route between source and destination that
has two conditions:
A. It moves in same direction with source and/or
destination.
B. Intermediate node’s location is between source and
destination.
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Method description



Algorithm No.1 describes next hop selection according to
the above criteria.
The algorithm determines whether a candidate node can
be an intermediate in route between source and
destination.
Get_Direction function returns direction of input node
and Get_Position function returns location of any input
nodes in network.
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Method description

Routes established by this way are more stable and have
less overhead than original routing method.

There is one problem : maybe we cannot find any
intermediate node as next hop for routes having these
restrictions.
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Method description

For solving this problem, we change our strategy.

Firstly, we put lower bound on number of discovered
routes and then divide algorithm into two steps:
In step one, protocol searches for nodes that have both
condition of position and direction.
If the results satisfy lower bound of routes, algorithm
without doing anything will finish and do other routing
phases such as route maintenance and data transmission.


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Method description

In step2,algorithm removes position condition and all
nodes that are in same direction with source and/or
destination, can be selected as intermediate nodes for
route.
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Simulation environment




Our simulation has been done in a 1000m×1000m area
and for 700 second. Simulation area contains 3 horizontal
streets, 3 vertical streets and 9 intersections.
Each street has 2 lane and we do not supposed any traffic
lights at intersections.
Maximum speed when the number of nodes changes is
20m/s and acceleration is 5m/s2.
Transmission range of each node is 250meters and 802.11
used as a MAC layer protocol.
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Simulation parameter
A. Link Expiration Time (LET)
 We suppose that transmission range of every node is R.
We also need node’s speed to calculate LET.
 Suppose we want calculate LET between node i and j.
distance between them is |di,j| and velocity of each node is
vi and vj.
 Base of these parameters and if nodes move in same
direction, we have:
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Simulation parameter

If two nodes are moving in opposite direction,equation 2
will be change to equation 3:

After calculation of LET, we can obtain RET (Route
Expiration Time). RET for a route is minimum LETs that
make that route:
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Simulation parameter
B. Broken links
 Route is more stable if it has less broken link in any
connection. We use this parameter to show route stability.


If the number of broken link per route is low,route is more
stable.
High broken link leads to exchange more control packet
and have more packet loss than route with lower broken
link.
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Simulation parameter
C. Route length
 Route length determines by number of hops that every
source nodes needs to traverse until reach a destination.
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Simulation results
A. Link stability
 A link is stable if its nodes satisfying these three
conditions; their moving directions are same, their
positions are in acceptable states, and finally difference of
their velocity is endurable with regard to their positions
and direction
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Simulation results


Figure 2, depicts number of broken links between source
and destination with respect to change network density in
our simulation environment.
In this experiment, we have compared our method,
DAODV, with original AODV.
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Simulation results

As depicted in figure 3, DAODV behaves uniformly on
changing of node’s speed. In AODV, number of broken
links increase faster than DAODV in high velocities.
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Simulation results
B. Route length
 Number of hops between source and destination
determines route length. Our solution tries to reduce
number of hops to shorten route lengths between source
and destination.
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Simulation results

Figure 4 demonstrates that in our method, route lengths
are shorter than AODV routes. The improvement is about
30% in average.
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Simulation results

As depicted in figure 5, our method is also sensitive to
nodes velocities. It works well for the applications, which
demands high-speed nodes, and selects shorter routes than
AODV.
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Simulation results
C. Route Expiration Time (RET)
 Figure 6 shows Route Expiration Time (RET) versus
network density. As depicted in this figure,increasing the
number of nodes leads to decrease RET.
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Simulation results

Figure 7 shows that DAODV by changing speed of nodes
is also more stable than AODV.
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Conclusion

In this paper, we have proposed DAODV protocol that
improves the performance issues on common AODV
protocol.

The main goal of DAODV is to establish more stable
routes especially in the applications that demand high
mobility of nodes such as VANETs.
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Conclusion

The proposed method uses two important parameters of
movement (direction and position) to select next hops
during route discovery phase.

Finally,our simulation experiments showed that DAODV
protocol works well in various traffic situations.
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