Improvised Routing Capability in Mobile Wireless
Ad-Hoc Networks
Saurav Ghosh & Shruthi P.C.
Dept of TCE, Dr. AIT, Bangalore, India
E-mail : sauravgsh16@gmail.com, pcshruti@gmail.com
Abstract – The following paper presents an algorithm that
includes mobility in the routing protocols which helps in
reducing the packet losses in mobile ad hoc networks
(MANETs). The route life time decreases as the degree of
mobility of the route increases. This decrease of the route
life time causes frequent link failure thus resulting in more
packet loss and low throughput. This requires
retransmission of packets which further overloads the
network and causes additional latency and packet loss. The
algorithm proposed in the following paper attempts to
estimate the number of packets that can traverse though
the route before it breaks because of mobility. The
simulation result shows that the packet delivery ratio can
be improved up.
I.
RLT and allows the protocol to send number of packets
that can traverse successfully to the desired destination
within the specified RLT period. This provision is thus
shown to be effective in improving the performance of
routing in MANETs.
II. LITERATURE SURVEY
A. An Upper Bound on Network Size in Mobile Ad Hoc
Networks: The paper proposes a model to compute an
upper bound for the maximum network size in mobile
ad-hoc networks. In MANETs, nodes are free to move
and organize without involving any infrastructure or
centralized administration. Due to the limited
transmission range of wireless radio transceivers, there
is a need for intermediate nodes, working as relays, to
establish a communication path between sourcedestination pairs in the network. The proposed algorithm
applies directly to reactive routing protocols.
INTRODUCTION
A Mobile Ad-hoc Network (MANET) consists of
a collection of mobile nodes connected by wireless
links. One of the major challenges in mobile ad hoc
networks (MANETs) is link failure due to the mobility.
Because nodes in a MANET act as routers for any
ongoing packet communication and have limited
transmission ranges, the communication links are
broken which causes packet loss to occur. This problem
gets amplified when the route consists several such
links. When links break down it causes a series of
undesirable events and outcomes. If the duration of
operability of the link can be predicted, then the routing
protocol can use this to an advantage. Every link can be
connected to for a limited amount of time, called link
life time (LLT), and the life time of a route, called route
life time (RLT). The RLT in turn depends of the LLT
which is taken to be the lowest LLT. The increase of the
degree of mobility causes the LLTs to decrease which
eventually causes the RTL to decrease. This causes the
increase of packet loss and low throughputs.
The protocols are composed of two main mechanisms:
a) Route Discovery is the mechanism by which a source
node S, attempting to send data packets to a destination
node D, discovers a route to node D.
b) Route Maintenance is the mechanism by which nodes
detect and locally repair any broken route that had been
initially discovered and established by the route
discovery mechanism.
Advantage:
This
algorithm
guarantees
the
communication path from source to destination in a
network by limiting the maximum route count to hopcount under the bound limit.
B. Mobility-Adaptive Protocols for Managing Large Ad
hoc Networks: The paper proposes a new protocol for
efficiently managing large ad hoc networks, i.e.,
networks in which all nodes can be mobile. Since nodes
in such networks are not necessarily equal in that they
Advantage: The algorithm presented utilizes
mobility to decrease the packet loss in the network.
Thus, the proposed algorithm makes an estimate of the
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may have different resources, not all of them should be
involved in basic network operations such as packet
forwarding, flooding, etc. In the proposed protocol, a
small subset of the network nodes is selected based on
their status and they are organized to form a backbone.
The protocol is thus named backbone-protocol or Bprotocol. Here each node is capable of monitoring a
given surrounding area (sensing), and coordinating with
the other nodes in the wireless network to achieve a
larger sensing task. Here rather than considering each
node in the network equally, an efficient management of
network resources can be obtained by deploying only a
subset of the network nodes. Only those nodes whose
local status allows them to guarantee reliable
communication among them, and with any other node,
will be selected to form a network dynamically
superimposed over the flat network.
more radio interference, channel contention, and energy
consumption, which may seriously degrade the
utilization of the network resources. Therefore, to
achieve the desired network performance, it is necessary
to investigate the property of node mobility and its
effect on topology dynamics of MANETs. The topology
dynamics is investigated by analyzing two key topology
metrics: expected link lifetime and expected link change
rate.
Advantage: The topology is based on the
assumption of smooth mobility model wherein the
mobile nodes smoothly change their velocity of
movement avoiding the random behavior of movement.
The expected link lifetime and expected link change
rate gives us the rate of change of links and the link’s
life time thus allowing the topology matrices to be
utilized to estimate network connectivity.
The proposed B-protocol comprises two major
tasks. B-nodes selection, to select the backbone nodes
(B-nodes).These nodes are in charge to “serve” all the
other non selected nodes (we term these nodes F-nodes,
i.e., nodes that belong to the flat network and not to the
B-network). B-links establishment, where backbone
links (B-links, i.e., links among the B-nodes) are
established so that the resulting B-network is always
connected.
D. Analyzing the Impact of Mobility in Ad hoc
Networks: The paper shows how the mobility of a node
impacts the ad hoc networks. Since not so many
MANETs have been deployed yet, most of the research
in this area is based on simulations. Among the
multitude of simulation parameters (traffic and
communication pattern, mobility model, propagation
model, etc.), the mobility model has a major impact on
the link and route lifetime distribution, and therefore
also on the protocol and application performance.
Hence, for an efficient design of MAC and network
protocols, one has to understand the impact of the node
mobility on the link and route lifetimes.
Advantage: The task of selecting the B-node is
performed at each node based on a node’s own weight.
The highest the weight of a node, the more suitable that
node is for being a B-node.
C. Analyzing Topology Dynamics in Ad hoc Networks
Using a Smooth Mobility Model: The topology
dynamics based on a smooth model is analyzed, because
it generates smooth nodal movements, has no speed
decay problem, and maintains a uniform spatial node
distribution. Two topology metrics are studied expected
link lifetime and expected link change rate by using a
distance transition probability matrix P, in which an
element represents the distance change between two
neighboring nodes. The existence of a link based on the
present distance between a pair of nodes and their
relative speed.
This paper studies and analyzes the impact of
human mobility on the link and route lifetime
distributions in a real MANET. The collected data from
this test network is used to analyze the impact of human
mobility on the link and route lifetimes. However, the
lifetime of links and routes is not only determined by
user mobility but also by different sources of failures
like packet collisions, or interference from any sender
emitting at the same frequency band. In the absence of
motion or location detection sensors, it is not directly
possible to distinguish with IEEE 802.11b hardware
between link failures due to human mobility or due to a
collision/interference failure.
In mobile ad hoc networks (MANETs), node
mobility induces the network topology to change
randomly and rapidly at unpredictable times which
cause the network topology to be vulnerable to frequent
link failure and network partitioning, thus could incur
substantial routing overhead, excessive transmission
delay and packet loss among mobile nodes. Hence, in
order to design mobility resilient MANET, a solution is
to enlarge the transmission range of the mobile wireless
devices for reducing the network topology change rate.
However, by this way, the mobile nodes would suffer
To solve this problem, a statistical framework is
developed which allows for analyzing the link and route
lifetimes while distinguishing between the two causes of
failures.
Errors and errors due to mobility, and determine the
distribution of each error type.
There are two statistical view points to look at link
and route lifetimes:
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a)
The total lifetime of a link or route describes the
time interval between the moment the link (or
route) appeared until it breaks.
because it retains no knowledge concerning its past
locations and speed values. The current speed and
direction of an MN is independent of its past speed and
direction. This characteristic can generate unrealistic
movements such as sudden stops and sharp turns
b) The residual lifetime represents the time interval
between a sample moment after the creation until
the link or path breaks
b) Random Waypoint Mobility Model: This model
includes pause times between changes in destination and
speed. An MN begins by staying in one location for a
certain period of time (i.e., a pause time). Once this time
expires, the MN chooses a random destination in the
simulation area and a speed that is uniformly distributed
between [minspeed, maxspeed]. Speed of the MN in the
figure is uniformly chosen between 0 and 10 m/s. The
movement pattern of an MN using the Random
Waypoint Mobility Model is similar to the Random
Walk Mobility Model if pause time is zero.
From an application or user perspective, it is more
interesting to look at the residual lifetime since
communication starts at arbitrary moments and not
necessarily when a new route becomes available.
General Framework for Residual Lifetimes: To
determine the impact of mobility, the possible failure
reasons are separated into two classes:
a) Failures which are due to node mobility and
b) Failures which are independent of node mobility like
collisions or interference.
c) Random Direction Mobility Model: This model forces
MNs to travel to the edge of the simulation area before
changing direction and speed. The Random Direction
Mobility Model was created to overcome density waves
in the average number of neighbors produced by the
Random Waypoint Mobility Model. A density wave is
the clustering of nodes in one part of the simulation
area. In the case of the Random Waypoint Mobility
Model, this clustering occurs near the center of the
simulation area. In the Random Waypoint Mobility
Model, the probability of an MN choosing a new
destination that is located in the center of the simulation
area, or a destination which requires travel through the
middle of the simulation area, is high. Thus, the MNs
appear to converge, disperse, and converge again
The corresponding failure probabilities are defined as
follows:
a) pn(t) = P[T < t]: The probability that the link between
two nodes breaks due to movement of one of the two
nodes.
b) pl(t) = P[T < t]: The probability that the link between
two nodes breaks due to disturbances from other
devices. They might be packet collisions from other
nodes competing for the wireless channel, or general
interference from other sources sending at the same
frequency.
With these two independent failure probabilities, the
formulation of the overall lifetime probability of a link
is possible.
d) A Boundless Simulation Area Mobility Model: A
model that converts a 2D rectangular simulation area
into a torus-shaped simulation area. In the Boundless
Simulation Area Mobility Model, a relationship between
the previous direction of travel and velocity of an MN
with its current direction of travel and velocity exists
[12]. A velocity vector v = (v;q) is used to describe an
MN’s velocity v as well as its direction q; the MN’s
position is represented as (x; y). Both the velocity vector
and the position are updated at every Dt time steps
according to the following formulas:
E. Special issue on mobile ad hoc networking;
Research, trends and applications: This paper is a
survey of mobility models that are used in the
simulations of ad hoc networks. Several mobility
models that represent mobile nodes whose movements
are independent of each other (i.e., entity mobility
models) and several mobility models that represent
mobile nodes whose movements are dependent on each
other (i.e., group mobility models) are described. The
goal of this paper is to present a number of mobility
models in order to offer researchers more informed
choices when they are deciding upon a mobility model
to use in their performance evaluations
v(t +Dt) = min[max(v(t)+Dv;0);Vmax];
q(t +Dt) = q(t)+Dq;
x(t +Dt) = x(t)+v(t) _ cosq(t);
y(t +Dt) = y(t)+v(t) _ sinq(t);
Seven different synthetic entity mobility models for ad
hoc networks are discussed:
where, Vmax is the maximum velocity, Dv is the change
in velocity which is uniformly distributed between [Amax *Dt; Amax *Dt], Amax is the maximum
acceleration of a given MN, Dq is the change in
direction which is uniformly distributed between [-a *
a) Random Walk Mobility Model (including its many
derivatives): It is a simple mobility model based on
random directions and speeds. The Random Walk
Mobility Model is a memory less mobility pattern
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Dt;a * Dt], and a is the maximum angular change in the
direction.
b) Mobility Algorithm: The algorithm solves the
mobility related routing problems in the following four
steps:
III. METHODOLOGY
1. Source estimates a minimum threshold link lifetime:
In any on-demand routing protocol, routes that are used
for sending data packets are discovered based on some
requirements (i.e., routing metrics). In the proposed
mobility scheme, the source uses a minimum threshold
link life time (TLLT) to discover more stable links and
routes. The source estimates TLLT based on the nature
of mobility. Unlike highway, random mobility scenario
prevails in urban area. Routes in a highway mobility
scenario are more stable compared to routes in a random
mobility scenario. Thus, TLLT can be set higher for
highways compared to a random mobility scenario.
TLLT in a random mobility scenario can be set higher
for low speeds compared to high speeds.
In order to reduce packet loss due to link failures,
mobility needs to be integrated in routing protocols.
This integration needs to be independent of routing
protocols to have an effective solution. The scheme is
based on an efficient use of the duration of connectivity
of two neighboring nodes in a route known as the link
life time (LLT).
The scheme makes use of the following methods in
order to implement the proposed methodology:
2. Using TLLT in route discovery process to detect
unstable routes: In case of any on-demand routing
protocol, whenever the source has a packet to send, it
searches a route in the route cache. If there is no route
available in the cache, the node sends a route discovery
packet to a desired destination. Here the source sends
TLLT in the route discovery packet.
Each node along the path toward the destination
calculates its own LLT with the previous node, and
compares the calculated LLT with the TLLT in the
packet. If the calculated LLT is greater than the TLLT
of the packet, this node becomes a part of the route.
3. Determination of route life time: It is essential to
estimate the duration “route life time (RLT)”. It is
defined as the duration of the liveliness of any route. All
the nodes in any route have their own LLTs, and the
node with the lowest LLT has higher probability of
breaking the route. So, the lowest LLT in any route is
the RLT. RLT is given by
RLTnet = RLT– troute.
4. Algorithm for reducing packet loss due to mobility
using RLT: The route discovery process with mobility
Figure: A scenario for calculating LLT
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assisted routing is explained in Step 3. Whenever there
is packet to send, the source finds a route from the route
cache, and sends an estimated number of packets that
the respective route is able to deliver before breaking.
Latency between source and destination, troute, is
important as well. That is needed to estimate the number
of packets that can be sent by the source to the
destination. Let us assume Nest be the estimated number
of packets to be sent through that route, and given by
b) AODV retains the desirable feature of DSR that
routes are maintained only between nodes which need to
communicate.
Nest = RLTnet/ troute .
2) The mobility of a ad-hoc network can be extended to
a large extent without causing much increase in latency
due to the retransmission of packets dropped.
V. APPLICATIONS
1) The proposed system can be used to reduce the data
lost due to unavoidable dropping of packets from the
network when nodes are mobile.
The selected route remains alive during RLT net, and
within this RLTnet, the source will be able to send
approximately Nest number of packets. If the source
sends more than Nest packets, the additional packets
have higher probability of getting lost. After finding
Nest, the packets are sent in order. If there are more
packets to be sent, the source finds an alternative route
from the route cache, and repeats the process for this
route by calculating its Nest. If there is no route
available in the route cache, the source starts the route
discovery process.
VI. CONCLUSION
This algorithm increases network throughput and
packet delivery rate. This algorithm applicable to any
on-demand routing protocol. The algorithm is
implemented in Ad hoc On-demand Distance vector
(AODV) protocol and in simulated in Network
Simulator-2.
VII. REFERENCES
Algorithm for routing integrated with mobility is shown
below:
IV. ENCHANCEMENTS
[1]
R.S. Chang, and W.W. Chen, “Mobility Assessment
On-Demand (MAOD) Routing Protocol for Mobile Ad
hoc Networks”, Journal of Wireless Communications
& Mobile Computing, Pages: 369 – 381, Vol. 4, Issue
4, Jun 2004, ISSN: 1530-8669.
[2]
M. Pascoe, J. Gomez, V. Rangel, and M. LopezGuerrero, “An Upper Bound on Network Size in
Mobile Ad Hoc Networks”, Proc. of IEEE
GLOBECOM, Pages 314-319, New Orleans, Nov
2008.
[3]
S. Basagni, D. Turgut, and S.K. Das, “MobilityAdaptive Protocols for Managing Large Ad hoc
Networks”, Proc. of IEEE International Conference on
Communications, Pages 1539-1543, Vol. 5, 2001.
[4]
M. Zhao, and W. Wang, “Analyzing Topology
Dynamics in Ad hoc Networks Using a Smooth
Mobility Model”, Proc. of IEEE WCNC, Pages 32793284, Kowloon, Hong Kong, Mar 2007.
[5]
D. B. Johnson, and D. A. Maltz, “Dynamic Source
Routing in Ad hoc Wireless Networks”, Mobile
Computing, Eds. Kluwer Academic Publishers, Pages
153-181, Vol. 353, 1996.
[6]
T. Camp, J. Boleng, and V. Davies. “A Survey of
Mobility Models for Ad Hoc Network Research”. In
Wireless Communications and Mobile Computing
(WCMC): Special issue on mobile ad hoc networking:
research, trends and applications, volume 2, pages
483–502, 2002.
[7]
V. Lenders, and J. Wagner, “Analyzing the Impact of
Mobility in Ad hoc Networks”, Proc. of REALMAN,
Pages 39-46, Florence, Italy, May 06.
Previous papers have used the Dynamic Source
Routing protocol in creating a solution for the problem
defined, whereas in this paper we have used the AODV
routing protocol.
Advantages of AODV
a) AODV attempts to improve on DSR by maintaining
routing tables at the nodes, so that data packets do not
have to contain routes.
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