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Int. J. Engg. Res. & Sci. & Tech. 2014 Pradeep Kumar K G and Neelima B, 2014
ISSN 2319-5991 www.ijerst.com
Vol. 3, No. 3, August, 2014
© 2014 IJERST. All Rights Reserved
Research Paper
SELF ORGANIZATION OF NODES IN BOUNDARYLESSMOBILE ADHOC NETWORKS
Pradeep Kumar K G1* and Neelima B2
*Corresponding Author: Pradeep Kumar K G, � [email protected]
Mobile ad-hoc network is a network where the nodes are capable of moving anywhere in adefined environment. In a real time scenario such as wildlife movement surveys, militaryoperations, emergency medical situations etc where nodes tend to move out off the definedboundary, is not well handled in the current technologies. Therefore in this paper, a novel methodis proposed to organize the movement of ad-hoc nodes. Here, a network with no-boundary isconsidered for the movement of nodes. Self-organization of the nodes is achieved throughAttraction and Repulsion movements. The proposed technique is implemented using NetworkSimulator NS2. From the simulation it is observed that the proposed technique increasesconnectivity and hence throughput increases.
Keywords: MANET, Attraction, Repulsion, Self organization, Throughput
1 Department of Computer Science and Engineering, SDM Institute of Technology, Ujire, Karnataka, India.2 Department of Computer Science and Engineering, N.M.A.M. Institute of Technology, Nitte, Karnataka, India.
INTRODUCTION
A Mobile Ad Hoc Network is also called MANET.
It is a set of mobile devices as shown in Figure 1.
The mobile devices are connected by a wireless
network and they are dynamic in nature. “Ad Hoc”
is derived from the Latin word which means “for
this purpose”. The mobile devices are capable
of configuring themselves and are called “self-
configuring” devices. They form a random
topology without making use of an existing
infrastructure (Nevadita Chatterjee et al., 2006).
The mobile devices cooperate with each other in
order to achieve the certain set of task. This
allows the users to maintain connectivity to thefixed network or to exchange information with the
base station or the access point that is available.
Figure 1: Mobile Ad Hoc Network
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Int. J. Engg. Res. & Sci. & Tech. 2014 Pradeep Kumar K G and Neelima B, 2014
The multi-hop communication allows achieving
this connectivity. The intermediate nodes are
considered as relays and the nodes use these
relays to reach distant destinations. The dynamic
nature and the ability to configure themselves
allows the nodes to change location and still
maintain the connectivity. Each node acts as
router for another node. There exist many
algorithms that determine the mobility pattern, i.e.,
the node movements.
Mobility of the mobile nodes has a significant
importance as it greatly determines the
performance of the MANET (Ivan Stojmenovic
and John Wiley & Sons, 2002); (C F Garca-
Hernndez et al., 2007).
The mobility models are broadly classified as
below (Savyasachi Samal, 2003).
• Deterministic model - urban traffic model
• Semi-deterministic model - column model
• Random - Brownian motion
Figure 2 shows the deterministic mobility
model. This model is the most simplest type of
model. The type of motion in this model is
predictable and the devices follow the predefined
path. For example, if the mobile nodes are moving
in a straight-line (i.e., following a deterministic
model), then the deviation of the direction vectors
associated with any two positions would be zero,
as the mobile nodes continue to move in the same
direction. Sample scenario is cars moving in
urban traffic area.
Semi-deterministic model does not follow a
strict deterministic pattern. They do follow a
pattern and the path varies to some extent; a
general pattern still does exist. Example, a
battalion on battle tanks marching ahead. This
model is as shown in Figure 3.
Random mobility pattern has a total stateless
motion pattern. The future movement of the node
is completely independent of the past movement
and hence no bounds are imposed on the next
movement to be chosen. This randomness in
choosing the next direction vector renders this
type of motion completely unpredictable. The
Figure 4 shows this model.
The nodes are free to move randomly. Thus
the network’s wireless topology may be
unpredictable and change rapidly. They require
minimum configuration and the deployment is
quick and the central governing system does not
exist and all the above makes the ad hoc
Figure 3: Semi-deterministic Model
Figure 2: Deterministic Model
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Int. J. Engg. Res. & Sci. & Tech. 2014 Pradeep Kumar K G and Neelima B, 2014
networks more suitable for emergency situations
like natural disasters, military conflicts,
emergency medical situations, to track wildlife
animal movements etc (Sahin CS et al., 2009).
An ad-hoc network is a dynamic multi hop
wireless network that is established by a set of
mobile nodes. Such networks are, therefore,
suitable for the environments where it is a difficult
to create a fixed infrastructure. In this network,
mobile nodes randomly move and communicate
over radio channels. If two mobile nodes are in a
radio transmission range, they can communicate
with each other directly, otherwise, the source
node sends/receives the packets via some
intermediate nodes (Naouel Ben Salem and
Jean-Pierre Hubaux, 2006).
Self-organizing nodes are the major
contribution of the MANETS (Sahin CS et al.,
2008). The nodes in MANET when compared to
traditional ad hoc networks are expected to be
dynamic. The following Figure 5 depicts self
organized nodes. By dynamic, it means that the
nodes are allowed to move in any direction within
a certain geographical area. The nodes move
dynamically and there is continuous establish-
ment and breaking of the links. When a node
comes closer to another node, it breaks its link
with the previous node and establishes the link
with the new node.
In an unlimited geographical area, the
boundary is removed and random movements
of nodes in MANETs are generated (Eli De
Poorter et al. 2011); (ITU Reports, 2005); (Sahin
CS et al., 2009). The node density is maintained
during the random movement of nodes. The
nodes should keep moving and should stay in
the same area and not run away. The Attraction
& Repulsion algorithm are used to maintain the
connectivity between the nodes.
The connectivity among the nodes may differ
with time due to nodes that are randomly moving
and may join or leave the network at any time.
Hence, an efficient routing protocol is needed to
allow communication over dynamic MANET
topology. Several ad hoc routing protocols have
been proposed and implemented to determine
the most efficient path to route information
through dynamic nodes in MANET. Meanwhile,
since most of the mobile nodes have different
Quality of Service (QoS) requirements, recent
research work of MANET routing has focused on
developing protocol that is able to support various
QoS requirements. In this study, a new routing
protocol namely EMNet has been proposed to
cater for different QoS requirements in MANET.
It was designed based on an artificial intelligent
technique namely Electromagnetic-like
Figure 5: Self Organized NodesFigure 4: Random Model
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Int. J. Engg. Res. & Sci. & Tech. 2014 Pradeep Kumar K G and Neelima B, 2014
Mechanism (EM), which simulating the attraction-repulsion mechanism theory of electro-magnetism. The EM generated solutions for newpath establishment and broken links restorationby regenerating new individuals with qualityimprovement through its attraction-repulsionprocess. The new EMNet protocol has beensimulated in various MANET scenarios and itsperformance in routing was compared withconventional ad-hoc On-demand Distance Vector(AODV) routing protocol. The simulation resultsshow that EMNet is able to achieve better resultsin terms of packet delivery, normalized routingload, end-to-end delay, overhead, and throughputin comparison with AODV in the simulationscenarios (Johnson R and Jasik H P, 1984).
The stochastic model assumed to govern themobility of nodes in a mobile ad hoc network hasbeen shown to significantly affect the network’scoverage, maximum throughput, and achievablethroughput-delay. Random walk model are usefulfor assessing the achievable event detectionrates in surveillance applications where wireless-sensor-equipped vehicles are used to detectevents of interest.
Mobile ad hoc networks (MANETs) enableusers to maintain connectivity to the fixed networkor exchange information when no infrastructure,such as a base station or an access point, isavailable. This is achieved through multihopcommunications, which allow a node to reach faraway destinations by using intermediate nodesas relays.
The probabilities of path duration and pathavailability strongly depend on the mobility patternof the network nodes. Indeed, the path duration(availability) is determined by the duration(availability) of its links, which on its turn dependson the movement of a node with respect to the
other. To characterize the nodes position with res-
pect to each other, we need the spatial distribution
of a single node over time Figure 6.
Figure 6: Flowchart
RELATED WORK
The geographic area covered by a conventional
structure based network (e.g., cellular network,
WiFi network, etc.) is populated with base stations
(also called access points) that are connected to
each other via a backbone. A mobile node can
use the network when it has a direct (single-hop)
connection to a base station, but as soon as it is
beyond the reach of the base stations' coverage,
the mobile node is disconnected from the struc-
ture-based network. For the operator, the usual
solution to this problem consists in increasing the
coverage by adding antennas and for the user to
move until he reaches a covered region.
An alternative solution would be to allow multi-
hop communications in the structure-based
network, which would make it possible for the
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Int. J. Engg. Res. & Sci. & Tech. 2014 Pradeep Kumar K G and Neelima B, 2014
isolated node to ask other nodes to relay its traffic
to or from a base station (Ivan Stojmenovic and
John Wiley & Sons, 2002).
In Delay Tolerant networks, Node cooperation
is fundamental to ensure acceptable perfor-
mance: in fact, differently to more traditional (fully
connected) types of wireless multi-hop networks,
nodes are typically requested not only to act as
message forwarders, but also to store in their own
buffer other nodes’ messages for a very long time
interval (store-and-forward communication).
Thus, both energy and memory resources,
which are very limited in a typical mobile node,
has to be sacrificed for the other nodes’ good.So
the performance of common DTN routing proto-
cols under different levels of node cooperation
are characterized.
Nodes within a network transmit their own
information, and serve as relays to help other
nodes transmissions (Rohit Negi and Arjunan
Rajeswaran, 2003). Several energy-efficient
cooperative transmission schemes have been
investigated in (Philo Juang et al., 2002) charac-
terizing their outage behavior. Most existing
cooperative protocols operate in a time or
frequency-sharing manner, such that each node
sends its own messages and relays its partners'
messages in separate time/frequency slots.
ZebraNet is a wireless sensor network aimed
at wildlife tracking. The ZebraNet system includes
custom tracking collars (nodes) carried by
animals under study across a large, wild area;
the collars operate as a peer-to-peer network to
deliver logged data back to researchers. The
collars include global positioning system, flash
memory, wireless transceivers and a small CPU;
essentially each node is a small, wireless
computing device. Since there is no cellular
service or broadcast communication covering the
region where animals are studies, ad hoc peer-
to-peer routing is needed(Philo Juang et al.,
2002); (Ajay Koul et al., 2010); (Macker J P and
Corson M S, 2001); (C F Garca-Hernndez et al.,
2007).
The Terminodes project [4] is a long term
research project aimed at studying and
prototyping large scale self-organized mobile ad
hoc networks. Here the terminodes refer to
terminal and node. Self-organized networks
distinguish themselves from traditional mobile ad-
hoc networks, based on the traditional Internet
two level hierarchy routing architecture (S K Tiong
et al., 2012), by emphasizing their self-
organization peculiarities (JanuszKusyk et al.,
2011). Self-organized networks are non-authority
based networks, i.e., they can act in an indepen-dent way from any provider or common denomi-nator, such as the Internet, even if they still requireregulation (self-organization).
Self-organized networks are potentially verylarge and not regularly distributed. In principle,one single network can cover the entire world.Density is supposed to be very high in small areas(e.g. towns), and low in large areas (Sahin C S,2008); (Macker J P and Corson M S, 2001).
Self-organized networks are highly co-operative. The tasks at any layer are distributedover the nodes and any operation is the result ofthe cooperation of a group of them.
THE ATTRACTION &
REPULSION ALGORITHM
The node movement considered here in this israndom and the boundary restriction is removed.The node movement in general is guided by thealgorithms which consider the node mobilitywithin the network boundary. The attraction and
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Int. J. Engg. Res. & Sci. & Tech. 2014 Pradeep Kumar K G and Neelima B, 2014
repulsion algorithm works on the principle that,the nodes which move apart from each other bya predefined distance are repulsed and therepulsed nodes, establish a link with those nodesthat are nearby.
Here the minimum distance that is allowedbetween two nodes as “MinD” and the maximumdistance that the two nodes can be at as “MaxD”.The distance between the nodes is calculatedcontinuously; the node positions and thedistances are updated periodically in therespective routing table. During the randommovement, if two nodes happen to come neareach other and the distance between them is lessthan “MinD”, then the nodes are repulsed. Ifnodes drift apart from each other and the distanceexceeds “MaxD”, then the nodes are attracted.The distance is calculated using Euclidiandistance formula. In real time this algorithm wouldbe running infinitely. This is required to maintainconsistent connectivity.
The algorithms have been utilized to maintaincontinuous data transfer between nodes in thenetwork.
Algorithm: [The attraction & repulsion method]
1. Initialize the nodes with random movement inthe provided geographical area except node0 and node 1.
2. Calculate position of each node except node0 and node 1.
a. For every node except node 0 and 1, findout position of i’th node as (Xi, Yi)
b. For every node except node 0 and 1, findout position of j’th node as (Xj, Yj)
3. Display the node positions, used forcalculating the distance.
4. Calculate distance between two nodes usingeuclidian distance formula
d = (x2 – x
1)2 + (y
2 – y
1)2 (1)
5. If distance is less than MinD, it means thenodes are close to each other.
a. Select a random number for repulsion in Xcoordinates.
b. Select a random number for repulsion in Ycoordinates.
c. If j’th current node is greater than previousposition, moving towards (maxX, ---) thenrepulse back to (minX, ---) coordinates.
d. If j’th current node is greater than previousposition, moving towards (---, maxY) thenrepulse back to (---, minY) coordinates.
e. If j’th current node is less than previousposition, moving towards (minX, ---) thenrepulse back to (maxX, ---) coordinates.
f. If j’th current node is less than previousposition, moving towards (---, minY) thenrepulse back to (---, maxY) coordinates.
6. Make the position within the boundary ofsimulation area.
7. If nodes are far away for attraction, attract toinitial position by setting the position of node(Xi, Yi) coordinates.
8. Repeat the above steps to maintain coordi-nates, where nodes i and j are close enoughand not far from each other.
EXPERIMENTAL SETUP
The proposed Attraction & Repulsion algorithmis simulated using Network Simulator 2(NS2)(HaninAlmutairi et al., 2013).The simulationenvironment is summarized in the Table 1.
RESULT ANALYSIS
The Simulation was carried out by increasing thenumber of nodes in the sequence 10, 20, 30, 40,
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Int. J. Engg. Res. & Sci. & Tech. 2014 Pradeep Kumar K G and Neelima B, 2014
50, 60, 70, 80, 90, 100 for better understanding
and comparison. The simulation also considers
the bounded network and thus a comparison is
being made. The simulation and the analysis
clearly show the advantages and benefits of
moving from bounded network to boundary-less
network.
The Figure 7 shows the ratio of the number of
packets delivered to the destination. The number
of nodes delivered with bounded simulation is
less and the overall performance shows the
improved packet received ratio against the total
number of nodes. As the number of nodes
increases, there is better delivery of packets and
in turn reducing the number of packets lost with
boundary less simulation. During emergency
situations the boundary less network provides
better connectivity.
Figure 8 depicts the total number of packets
dropped during the simulation. Packet drop
occurs when one or more packet fails to reach
their destination. Packet drop is closely linked with
the quality of service. The performance of the
protocol is better as long as the packet drop value
is less. In our experiment it is observed that,
packet loss is reduced with more number of
nodes in case of boundary-less network. In case
of bounded network when the nodes move out
of the boundary, the connectivity is lost and hence
the packets get dropped to a larger extent.
However this is not the case in boundary-less
network since the boundary is removed and the
connectivity is maintained. Hence data is more
secure in this when more number of nodes are
present in the large geographical area, hence
better data delivery.
Figure 8: Number of Nodes vs. Total Packet Dropped
Figure 7: Number of Nodes vs. Total Packet Received
Simulation area (m x m) 1000x1000
Simulation time (s) 900
Min. Number of Nodes 10
MAC layer protocol 802.11
Maximum velocity (m/s) 50
Topology used Flat grid topology
Application layer protocol Constant bit rate
Table 1: Simulation Setup
Packet forwarding is the basic method of
transmitting the packet from source node to
destination node. The graph in Figure 9 shows
the total number of packets forwarded from the
source to destination. Routing is the process
where in the router/system decides destination
node to transmit the packet. Packet forwarding
is extensively used to keep unwanted traffic off
networks. In bounded network, if the nodes move
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Int. J. Engg. Res. & Sci. & Tech. 2014 Pradeep Kumar K G and Neelima B, 2014
Hop count refers to the number of hops to the
destination. It is a rough measure of distance
between two hosts. Hop counts are often useful
to find faults in a network, or to discover if routing
is indeed correct. Network utilities like Ping can
be used to determine the hop count to a specific
destination. This prevents packets from endlessly
bouncing around the network due to routing
errors. Both routers and bridges are capable of
managing hop counts, but other types of
intermediate devices (like hubs) are not. The
Figure 11 shows consistent hop count when
increase in number of nodes.
The graph in Figure 12 describes average hop
count. It is the average number of hops among
the shortest paths of all node pairs.
out of the boundary the link is lost and this
requires more packets to be forwarded in all
possible directions. This may lead to duplication
of packets and hence leading to more traffic. In
case of boundary-less network this does not
happen.
Figure 9: Number of Nodes vs.Total Packet Forwarded
Figure 10: Number of Nodes vs.Packet Delivery Ratio (%)
Packet delivery ratio (PDR) is defined as the
ratio of data packets received by the destinations
to those generated by the sources. The greater
value of packet delivery ratio means the better
performance of the protocol.
The Graph in Figure 10 shows the ratio of data
packets that are successfully delivered during
simulations time versus the number of nodes.
PDR =Total packets received
Total packets sent (2)
Figure 11: Number of Nodes vs.Total Hop Counts
Figure 12: Number of Nodes vs.Average Hop Count
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Int. J. Engg. Res. & Sci. & Tech. 2014 Pradeep Kumar K G and Neelima B, 2014
The throughput of network is the amount of
data transferred from source to destination in a
specified amount of time. Data transfer rates for
disk drives and networks are measured in terms
of throughput. Typically, throughputs are
measured in kbps, Mbps and Gbps. The average
hop count is reduced in the proposed technique.
The diagram in Figure 13 describes through
put is the rate of successful packet delivery over
a communication channel. This data may be
delivered over a certain node. The system
throughput or aggregate throughput is the sum
of the data rates that are delivered to all terminals
in a network.
BENEFITS & APPLICATIONS
The major advantages are as follows. Therandom movement proposed, provides betterconnectivity. The nodes will always be connectedand due to this, better throughput is achieved.The connectivity also ensures continuoustransmission which provides more appropriatedata for the analysis purpose. The count of nodesthat are required to cover larger geographicalarea is less. The lesser count of nodes in turnreduces the cost and leads to increasedefficiency.
The following are the major area ofapplications of proposed technique.
1. This would prove valuable in militaryapplications, especially during war whereimmediate action and data is required.
2. Understanding, analyzing and trackingwildlife movement by more appropriatedata.
3. Establishing better communication duringnatural calamities, since the movement israndom.
4. Unmanned vehicles have been recentlylaunched. The approach mentioned in thispaper can be used for better trafficmanagement in the coming future.
Figure 13: Number of Nodes vs.Throughput of Network (KBps)
The Figure 14 explains end-to-end delay. The
end-to-end delay of a packet is defined as the
time it takes to reach the destination after it is
locally generated at the source. The expected
end-to-end packet delay is obtained by averaging
over all packets of the n traffic flow in the long
term, and without incurring any ambiguity, it is
called the packet delay. The delay is more in
bounded network and thus the performance is
reduced.
Figure 14: Number of Nodes vs.Average End-to-End Delay
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Int. J. Engg. Res. & Sci. & Tech. 2014 Pradeep Kumar K G and Neelima B, 2014
CONCLUSION
The proposed attraction and repulsion algorithm
takes into consideration both the position based
technique and map based technique. The
previous position information is considered from
the routing table for the distance calculation. The
algorithm proposed has the advantages of better
efficiency and throughput. The packet drop is
considerably less and the cost involved is less. It
is also noted that packet delivery ratio increases
with the increase in nodes.
The only disadvantage that can be assumed
is the high traffic; however due to the long lasting
connectivity, this high traffic constraint can be
ignored.
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