ISSN XXXX XXXX © 2017 IJESC
Research Article
Volume 7 Issue No.3
Construction of K-Connected Dominating Set Algorithm for
Connecting the Wireless Nodes
S.Saranya1 , M.Revathi2 , V.R.Kav itha3
Head of the Depart ment 3
Depart ment of Co mputer Science & Engineering
Prathyusha Engineering College, Tamil Nadu, India
Abstract:
In order to construct a distortion less connectivity among the wireless networks by optimizing the area -based connected dominating
set over MANET by considering more heterogeneity, this paper proposes a novel k-connected dominating set construction and
maintenance algorithm. The algorithm is divided into three phases:1) Area Partit ion; 2) Area Expansion; 3) Area Connection. A t last,
the simulation is implemented with NS3 and the results are analysed in detailed with Message Overhead, Average end -to-end delay,
Throughput and Packet Delivery Ratio.
Keywords: connected dominating set, distortion less connection, heterogeneity, MANET, wireless network.
I.
INTRODUCTION
A MANET (mob ile ad hoc network) is a self-configuring
infrastructure less network of mob ile devices connected by
wireless. Thus, MANET (mobile ad hoc network) is applied in
ubiquitous network to create a s mart space (e.g Smart Grid, a
home or campus) called a ubiquitous stub environment where
users can enjoy ubiquitous service in an “anytime, anywhere, on
any device” manner. How to achieve good performance and
keep load on the hosts as low as possible become main problem
in MANET. Since MANET is an infrastructure less network, it
does not have a centralized control. This becomes an main
challenge in MANET. The other challenges of MANET are
fading, path loss, blockage, interference due to the transmission
impidents. Loss of packets during transmission in MANET.
Broadcasting is an common approach wh ich is used to solve
routing problem, and a straight broadcasting by global flooding
would lead to notorious broadcast storm problem, which
flooding may result in e xcessive redundancy, contention and
collision. K-CDS ( K-Connected Dominating Set ) is an
promising approach to broadcast routing overhead by reducing
rebroadcast or redundant broadcast, as the number of hosts
responsible for routing is reduced to the number of hosts in
backbone. Thus this paper is used to solve an MCDS (M inimu m
Connected Dominating Set) prob lem. To solve it, we meet the
following challenges:
Ho w to design an effective algorithm for constructing KCDS
over MANET.
How to dynamically maintain KCDS if any path gets distorted
over MANET.
To address those challenges, a novel K-CDS (K-Connected
Do minating Set ) construction, routes to nearest stronger path if
any distortion occurs in the network during communicat ion and
all the possible paths where determined using the spanning tree
algorith m. Our proposed K-CDS consists of three phases: 1)
International Journal of Engineering Science and Computing, March 2017
Area Partition 2) Area Expansion 3) Area Connection. The
simu lation is imp lemented with NS3. And the results are
analyzed in detail with Packet Delivery Ratio, Throughput,
Average end-to-end delay and Message Overhead.
II.
RELATED WORK
For this problem the existing theoretical analysis suggests that
the throughput for each node declines rapid ly towards zero as the
number of node rises. Therefore many solutions deal with the
issues on how to build the large sized ad hoc networks. A mong
these methodologies, network clustering is one of the
investigated approaches. The basic idea is to partition the nodes
into some groups which organize the network with several
logical areas. There is an extensive literature on construct of
MCDS over MA NET, such as Approximation algorith m, a
MCDS-based algorith m designed by Das, Greedy algorithm and
so on. However it is hard to gain global topology information in
large- sized networks that centralized approaches are not well
suited for large-sized networks. Additionally the algorith m finds
a rough CDS and then prunes some redundant nodes using two
rules (Rule 1 and 2), Dai and Wu later generalized pruning rule
by using K-neighbor coverage, called Ru le k [7], to further
reduce CDS size, fault tolerant k-connected m-do minating set
where either every node itself or its m-neighbors are in set, and
removal of k-1 nodes will not disconnect the induced graph of
set. A multicasting protocol is based on zone routing. Extending
the zone routing protocol (ZRP) presented by Hass and
Pearlman, Wang and Olariu designed a novel hybrid routing
protocol, called two zone routing protocol (TZRP). Chen
proposed a zonal algorith m for weakly connected dominating set
(WCDS) construction. Liang presented a hybrid virtual backbone
routing (VBR) framework for ad hoc networks with a variablesized zone hierarchy. Bo proposed an area algorithm for W CDS
construction. Later Bo extended his previous work by proposing
a novel zone algorith m (maximu m degree) with constant
approximation ratio, further reduced linear time and message
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complexity. Yin and Shi p roposed a distributed single-phase
algorith m (DSP) wh ich first selects a number of master nodes,
independently constructs each piece initiated fro m each master
by absorbing nodes. Later GUO Shaoyong, XING Ningzhe, FU
Ning, SHAO Sujie and YOU Fucheng proposed a novel area
based connected dominating set construction and maintenance
algorith m in ubiquitous environment (AB-CDS), which
maintains a stable structure over the large-scale MANET.
However, the above algorithms do not have an alternate solution,
if any path gets distorted. Therefore, this paper attempts to
research on K-CDS construction over MANET by considering
heterogeneity.
III.
K-CONNECTED
DOMINATING
CONSTRUCTION ALGORITHM
partitioned. After partitioning, if any new node enters an area
then that area is expanded by considering the CONNECTOR
node. The local sub areas were connected with the dominator
gateways connecting the adjacent area called Connector, by
considering the shortest path from source to destination. The
shortest path has been determined using the Euclidean Distance
formulae.
S ET
3.1 OVERVIEW
To obtain a distortion less connectivity among wireless network,
and K-CDS is constructed. As is mentioned above K-CDS this
paper consists of three phases: 1) Area Partition 2) Area
Expansion 3) Area Connection.
Figure. 1.Area Partiti on
3.2 AREA PARTITION
In this phase, the areas should be partitioned so that the local
areas should be identified. The local area was determined by
considering the neighbouring nodes as an area. Likewise several
local areas were identified by considering the neigh bouring
nodes with the hop neighbor information. After identifying the
local area the area should be partitioned. The area was
partitioned by considering the hop neighbouring informat ion. In
each area the Dominating nodes should be determined, that is the
nodes in an area should be reachable to all other nodes in the
network. A CDS is that, when the nodes in an area are ad jacent
to all other node set in the network.
Figure. 2.Area Expansion
3.2 AREA EXPANS ION
This phase is constructed after the area partitioning phase, such
that if any new node enters the area then that area should be
expanded. If an area has been expanded then that area dominated
node will get changed considering the neighbouring hop
informat ion and its energy value. The spanning tree algorithm is
constructed to avoid and to control the loops of the paths in an
network.
3.3 AREA CONNECTION
This phase is constructed after the expansion of area algorithm;
the area should be connected by identifying the Dominating
gateways connecting the adjacent area. Such that the local sub
area were connected by determining the Dominator gateways
connecting the adjacent area in each local sub area.
IV.
SIMULATION ENVIRONMENT
The simulation is done with NS3, in which nodes were identified
as local areas with the hop neighbor information. And in each
node the Dominator gateways connecting the adjacent area called
the CONNECTOR nodes were determined and the areas were
International Journal of Engineering Science and Computing, March 2017
Figure. 3. Area connection
IV.
RES ULT ANALYS IS
5.1 PACKET DELIVERY RATIO
We compare the K-CDS with the well-known algorith m ABCDS in terms of packet delivery ratio. A total number of packets
sent, in which the number of packets delivered.
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In the above figure when comparing K -CDS with the other
algorith m AB-CDS, the throughput is high in the K-CDS
algorith m.
5.4 AVERAGE END-TOEND DELAY
We compare the K-CDS algorith m with the other well-known
algorith m AB-CDS in terms of average end-to-end delay. The
time dealy is termed as how much time the message delayed to
be delivered successfully.
Figure. 4.packet deli very ratio
In the above figure when comparing K-CDS with the AB-CDS
algorith m, the packet delivery ratio is high in K-CDS algorithm.
5.2 MESSAGE OVERHEAD
We compare the K-CDS with the well-known algorith m ABCDS in terms of message overhead. The adding of the extra
padding bits to the message. The extra bits added to the message
should be low to have an efficient performance.
Figure. 7. Del ay
In the above figure, when comparing K-CDS with the other
algorith m A B-CDS the delay is less in the K-CDS algorithm.
VI.
Figure. 5.Message Overhead
In the above figure, when comparing K-CDS with the other
algorith m A B-CDS the message overhead is low in K-CDS.
5.3 THROUGHPUT
We compare the K-CDS with the well-known algorithm B-CDS
in terms of throughput. The rate at which the successful
transmission of messages. The throughput should be generally
more to have an efficient performance.
CONCLUS ION
In this paper, a novel K-CDS (K-Connected Dominating Set)
Construction is proposed over MANET. It first partitions the
network into local sub areas by considering the CONNECTOR
nodes and then expands the area if any new node enters an area.
Then the area is connected using the dominator gateway nodes
connecting the adjacent nodes called the CONNECTOR nodes.
It deals with heterogeneous nodes, if any distortion occurs in the
network, it will direct to the alternate strongest nearest path. The
alternative paths have been determined using the spanning tree
algorith m and the shortest path has been determined using the
Euclidean distance formula. This can be fu rther imp lemented as
an real t ime application.
VII. ACKNOWLEDGMENT
I am great ly thankful to Ms.V.R.Kav itha, Head of the
Depart ment, Co mputer Science and Engineering, who guided us
for doing this work. We are also thankful to our co llege for
providing us the needed materials.
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