cluster based routing protocol for ad hoc networks

Dr. N.S.Yadav
Assoc.Prof.
www.nshubforum.com
Department of Computer Science & Engineering
Sri Balaji College of Engineering & Technology, Jaipur
Performance Evaluation of Cluster Based
Routing Protocol in Ad hoc Networks
1

Contents
2
 Introduction
 Routing in mobile adhoc networks
 Performance evaluation of CBRP
 Conclusions and future scope

Introduction
3
 mobile ad hoc network is a collection of mobile nodes that utilize multi-
hop radio relaying and are capable of operating without any support from
fixed infrastructure
 Various authors defined MANET in many different ways and a more
precise definition* may be taken as reference, which states it as:
“MANET is an autonomous system of mobile routers (and associated hosts)
connected by wireless links - the union of which form an arbitrary graph.
The routers are free to move randomly and organize themselves
arbitrarily; thus, the network’s wireless topology may change rapidly and
unpredictably. Such a network may operate in a stand-alone fashion, or
may be connected to the larger Internet”.
*Joseph Macker and Scott Corson, “Mobile ad-hoc networks (manet)”,
http://www.ietf.org/proceedings/01dec/183.htm, December 2001.

Characteristics of Ad Hoc Networks
4
The most salient characteristics which should be considered by
protocol designers were addressed within the MANET working
group, listed in RFC 2501 and are summarized here:
 Distributed Operation
 Dynamic Topology
 Multi Hop Communications
 Changing Link Qualities
 Dependence on Battery life

Applications
5
 Military applications
 Collaborative and distributed computing
 Emergency operations
 Wireless sensor networks
 Hybrid wireless networks

Routing in mobile ad hoc networks
6
The routing protocol has two main functions:
 Selection of routes for various source destination pair
 The delivery of messages to their correct destination

Characteristics of routing protocols
7
 fully distributed
 adapt to frequent topology changes
 loop-free and free from stale routes
 utilize both unidirectional and bi-directional links
 localized and involve minimum number of nodes
 minimize the number of packet collisions
 converge to optimal routes quickly
 use scarce resources efficiently
 utilize multiple routes
 incorporate quality of service (QoS)

Routing classification
8
Routing Protocols for MANET
Based on Information Update
Mechanism Based on Topology
Reactive FlatProactive Cluster Based

Based on Information Update Mechanism
9
 Proactive or table- driven routing protocols
 Every node maintains the network topology information in
the form of routing tables, example DSDV
 Reactive or on- demand routing protocols
 Maintain routes only if needed example DSR
 Hybrid protocols
 Combine the best features of the above two categories
example ZRP

Based on Topology
10
 In a flat structure, all nodes in a network are at the same level
and have the same capability and responsibility. Flat structure
routing is simple and efficient for small networks. Example DSR
 In cluster-based routing the nodes in the network are
dynamically organized into partitions called clusters and then
the clusters are aggregated again into larger partitions called
superclusters and so on. Example CBRP

Clustering in Ad hoc network
11
 Dynamic routing plays an important role in the performance of a
Mobile Ad Hoc Networks (MANET).
 A flat structure exclusively based on proactive or reactive routing
schemes cannot perform well in a large dynamic MANET
 The communication overhead of proactive routing protocols is
O(n2), where n is the total number of mobile terminals in a
network.
 For a reactive routing scheme, the disturbing RREQ (route request)
and the considerable route setup delay become intolerable in the
presence of both a large number of nodes and mobility.
 Consequently, a hierarchical architecture (cluster- based) is
essential for achieving a basic performance guarantee in a large-
scale MANET.

Cluster Structure
12
CM
CM
CH
CM
CM
CM
CH
CH
GW
GW
GW
CM
GW
CH
Cluster member node
Gateway node
Cluster- Head node member node

Clustering in Ad hoc network
13
 In a clustering scheme the nodes in a adhoc network are divided into
different virtual groups, and they are allocated to the cluster according to
some rules.
 Under a cluster structure, mobile nodes may be assigned a different status
or function, such as clusterhead, clustergateway, or clustermember.
 A clusterhead normally serves as a local coordinator for its cluster,
performing intra-cluster transmission arrangement, data forwarding, and so
on.
 A clustergateway is a non-clusterhead node with inter-cluster links, so it
can access neighboring clusters and forward information between clusters.
 A clustermember is usually called an ordinary node, which is a non-
clusterhead node without any inter-cluster links

Motivation
14
 Clustering is important for a network to achieve scalability in presence
of a large number of mobile nodes and high mobility
 However, constructing and maintaining a cluster structure usually
requires additional control overhead compared to a flat-based structure
in an ad hoc wireless network.
 This additional control overhead involved in clustering is a key issue to
validate the effectiveness and scalability enhancement of a cluster
structure.

Contribution
15
 A flat architecture based Dynamic Source Routing (DSR), and
cluster architecture based Cluster Based Routing Protocol (CBRP)
are evaluated and compared in terms of
 packet delivery fraction,
 normalized routing load,
 average end to end delay,
 channel utilization and
 control overhead in terms of packets and bytes
by varying number of nodes per sq. km, traffic sources, mobility,
speed and network load. It is shown through results that CBRP is a
better routing protocol in the presence of large number of nodes,
increased network traffic and load.

DSR – Dynamic source routing
16
 on-demand routing protocol designed to restrict the bandwidth
consumed by control packets by eliminating the periodic table-update
messages required in the table-driven approach.
 beacon-less and hence does not require periodic hello packet.
 When node S wants to send a packet to node D, but does not know a
route to D, node S initiates a route discovery.
 Source node S floods Route Request (RREQ)
 Each node appends own identifier when forwarding RREQ
 Destination D on receiving first RREQ, sends a Route Reply (RREP)
 RREP is sent on a route obtained by reversing the route appended to
received RREQ
 If any link on a source route is broken, the source node is notified
using a route error RERR

CBRP - Cluster Based Routing Protocol
17
 In CBRP the nodes of a wireless network are divided into
clusters.
 The diameter of a cluster is only two hops and clusters can be
disjoint or overlapping.
 Each cluster elects one node as the clusterhead, responsible for
the routing process.
 Clusterheads communicate with each other through gateway
nodes.

Operation of CBRP
18
The operation of CBRP can be divided in three phases:
 Cluster formation
 Routing process
 Cluster maintenance

Cluster Formation
19
 At any time, a node is in one of the three states: a cluster
member (CM), a cluster head (CH), or undecided
(UNDECIDED).
 When a node comes up, it enters the undecided state and
broadcasts a Hello message.
 When a cluster-head gets this hello message it responds with a
triggered hello message immediately. When the undecided node
gets this message, it sets its state to member.
 If the undecided node times out, then it declares itself the
cluster-head, if it has bi-directional link to some neighbor
otherwise it remains in undecided state and repeats the process
again.

20
A node in undecided state changes its status to one of the three states: CH, CM or
UNDECIDED as per the state transition diagram
UNDECIDED STATE
Receiving Hello from
non –CH member
Times out
Receive Hello
from CH
Neighbor table
Update
u_timer
Is neighbour
table empty?
YES
Schedule new
u_timer
Send triggered
Hello as CH
Terminate u_timer
Neighbor table as CM
Update
NO
CH STATE CM STATE

21
When two clusterheads are within transmission range of each other, the one
satisfying the state transition diagram will continue in clusterhead CH state and
the other will give up its role as CH and acquire the status of cluster member
CM.
Receive Hello
from CH
Set c_timer
CH STATE
Receiving Hello from
non –CH member
c_timer
Neighbor table
Update
expires
Is still in contention
with other CH?
NO YES
CM STATE
Send triggered
Hello as CH
Is
my_CH_ID <
Other CH_IDYES
Send triggered
hello as CM
NO

22
A node in cluster member CM state changes its status to one of the three states:
CH, CM or UNDECIDED as per the state transition diagram
Receive Hello
Schedule u_timer
CM STATE
Last head lost
NO
YES
CH STATE
Send triggered
Hello as CH
Is
my__ID <
any_other_ID
Update
neighbor table
UNDECIDED STATE

Routing process
23
 The routing process works in two steps. First, it discovers a
route from a source node S to a destination node D, afterwards it
routes the packets.
 On receiving the request a clusterhead checks to see if the
destination is in its cluster.
 When the destination receives the request packet, it replies back
with the route that had been recorded in the request packet.
 While forwarding the packet if a node detects a broken link it
sends back an error message to the source and then uses local
repair mechanism.

Comparison of DSR and CBRP
Parameter DSR CBRP
Routing structure Flat Cluster
Hello messages No Yes
Multiple routes Yes No
Critical nodes No Yes
Route maintained Route Cache Route table at cluster-Head
Routing metric Shortest path or next available in route
cache
First available route
Time complexity (route discovery) O (2D) O (2D)
Time complexity (route maintenance) O (2D) O (2d)
Communication complexity (route discovery) O (2N) O (2C)
Communication complexity (route maintenance) O (2N) O (2n)
Advantages Multiple routes, beacon less cluster heads exchange routing information
Disadvantages Scalability problem, large delays Cluster maintenance
Abbreviations:
D = Diameter of the network
N = Number of nodes in the Network
d = Diameter of affected area
C = Number of Clusters
n = Number of affected nodes
24

Simulation Parameters
Parameter Stage I Stage II Stage III Stage IV
Number of nodes 150 150 150 30,60,90,120,150
Traffic type CBR (UDP) CBR (UDP) CBR (UDP) CBR (UDP)
Traffic sources 30% of nodes
70% of nodes
30% of nodes
70% of nodes
10%,30%,50%,70%, 90% of
nodes
30% of nodes
70% of nodes
Simulation time 300s 300s 300s 300s
Simulation area 2000 m x 500 m 2000 m x 500 m 2000 m x 500 m 2000 m x 500 m
Transmission range 250 m 250 m 250 m 250 m
Node movement model Random waypoint Random waypoint Random waypoint Random waypoint
Propagation model Two ray ground Two ray ground Two ray ground Two ray ground
Data payload 512 bytes/packet 512 bytes/packet 512 bytes/packet 512 bytes/packet
Packet rate 4 packets/sec 2,4,6,8,10 packets/sec 4 packets/sec 4 packets/sec
Node pause time 0,60,120,180, 240,300 s 0s highest mobility
300 s lowest mobility
0s highest mobility
0s highest mobility
Speed 10 m/s 10 m/s 10 m/s 10 m/s
Bandwidth 2 Mb/s 2 Mb/s 2 Mb/s 2 Mb/s
25

Performance Metrics
26
 Packet Delivery Fraction: The ratio of the data packets delivered to
the destinations to those generated by the sources.
 Channel utilization capacity: This metric gives the fraction of
channel capacity used for data transmitted by the network and is
computed as
where PR is the number of data packets received by the destination
nodes, SZ is the size of the data packets, SET is simulation end time
and BW is the nominal channel bandwidth.
  BWSET
SZPR
CU






27
 Average end-to-end delay: This includes all possible delays
caused by buffering during route discovery latency, queuing at
the interface queue, retransmission delays at the MAC, and
propagation and transfer times.
 Normalized routing load: The number of routing packets
transmitted per data packet delivered at the destination.
 Control Overhead: The total number of non data packets
transmitted by the protocol. It is an important measure for the
scalability of a protocol. If a protocol requires sending many
control packets, it will most likely cause congestion, collision,
data delay and increase energy consumption in larger networks.

Influence of node mobility
29
To observe the effect of node mobility on the performance of DSR
and CBRP for a network under different traffic scenarios a network
of 150 nodes is simulated over a network area of size 2000m × 500
m with parameters listed in Table in stage I and the simulation
results are presented in this section.

Packet Delivery Fraction
0
10
20
30
40
50
60
70
80
0 60 120 180 240 300
Pause time (sec)
Packetdeliveryfraction(%)
DSR
CBRP 0
5
10
15
20
25
30
35
40
45
0 60 120 180 240 300
Pause time (sec)
DSR
CBRP
30
(a) 30% sources (b) 70% sources
Packet delivery fraction as a function of Pause time and 30%, 70% traffic
sources.

Channel Utilization
0
2
4
6
8
10
12
14
0 60 120 180 240 300
Pause time (sec)
Channelutilization(%)
DSR
CBRP 0
2
4
6
8
10
12
14
16
18
0 60 120 180 240 300
Pause time (sec)
DSR
CBRP
31
Channel utilization as a function of Pause time and 30%, 70% traffic
sources.

Average End To End Delay
0
0.5
1
1.5
2
2.5
3
3.5
4
0 60 120 180 240 300
Pause time (sec)
averageendtoenddelay(sec)
DSR
CBRP 0
1
2
3
4
5
6
7
8
9
0 60 120 180 240 300
Pause time (sec)
averageendtoenddelay(sec)
DSR
CBRP
32
Average end to end delay as a function of Pause time and 30%, 70% traffic
sources.

Normalized Routing Load
0
1
2
3
4
5
6
7
8
0 60 120 180 240 300
Pause time (sec)
Normalizedroutingload
DSR
CBRP
0
2
4
6
8
10
12
14
16
18
20
0 60 120 180 240 300
Pause time (sec)
DSR
CBRP
33
Normalized routing load as a function of Pause time and 30%, 70% traffic
sources.

Control Overhead
0
10
20
30
40
50
60
70
80
90
0 60 120 180 240 300
Thousands
Pause time (sec)
Controloverhead(packets)
DSR
CBRP
0
20
40
60
80
100
120
140
160
180
0 60 120 180 240 300
Thousands
Pause time (sec)
DSR
CBRP
0
1
2
3
4
5
6
7
0 60 120 180 240 300
Millions
Pause time (sec)
Controloverhead(Bytes)
DSR
CBRP
0
2
4
6
8
10
12
14
0 60 120 180 240 300
Millions
Pause time (sec)Controloverhead(Bytes)
DSR
CBRP
34
Control Overhead as a function of Pause time and 30%, 70% traffic sources.

Influence of network load
35
In this section the results of the simulations carried out by varying
the number of packets transmitted per second from 2 to 10 with two
different pause times are presented separately with 30% and 70% of
the nodes forming the traffic.

0
20
40
60
80
100
120
2 4 6 8 10
Packets per sec
DSR, p = 0s CBRP, p = 0s
DSR, p = 300s CBRP, p = 300s
0
10
20
30
40
50
60
70
2 4 6 8 10
Packets per sec
DSR, p = 300s CBRP, p = 300s
36
Packet delivery fraction as a function of load and 30%, 70% traffic sources.

Channel Utilization
0
2
4
6
8
10
12
14
16
18
2 4 6 8 10
Packets per sec
DSR, p = 300s CBRP, p = 300s
0
2
4
6
8
10
12
14
16
18
20
2 4 6 8 10
Packets per sec
channelutilization(%)
DSR, p = 300s CBRP, p = 300s
37
Channel utilization as a function of Load and 30%, 70% traffic sources.

0
1
2
3
4
5
6
2 4 6 8 10
Packets per sec
Averageendtoenddelay(sec)
DSR, p = 300s CBRP, p = 300s
0
1
2
3
4
5
6
7
8
9
10
2 4 6 8 10
Packets per sec
DSR, p = 300s CBRP, p = 300s
38
Average end to end delay as a function of Load and 30%, 70% traffic sources.

0
1
2
3
4
5
6
7
8
9
10
2 4 6 8 10
Packets per sec
DSR, p = 300s CBRP, p = 300s
0
2
4
6
8
10
12
14
16
18
20
2 4 6 8 10
Packets per sec
DSR, p = 300s CBRP, p = 300s
39
Normalized routing load as a function of Load and 30%, 70% traffic sources.

Control Overhead
0
20
40
60
80
100
1 2 3 4 5
Thousands
Packets per sec
ControlOverhead
DSR, p = 300s CBRP, p = 300s
0
20
40
60
80
100
120
140
160
180
2 4 6 8 10
Thousands
Packets per sec
Controloverhead
DSR, p = 300s CBRP, p = 300s
0
1
2
3
4
5
6
7
8
2 4 6 8 10
Millions
Packets per sec
Controloverhead(bytes)
DSR, p = 300s CBRP, p = 300s
0
2
4
6
8
10
12
14
2 4 6 8 10
Millions
Packets per sec
DSR, p = 300s CBRP, p = 300s
40
Control Overhead as a function of Load and 30%, 70% traffic sources.

Influence of traffic sources
41
To observe the effect of number of traffic sources on the
performance of DSR and CBRP for a network, in constantly
changing network topology and in static case, a network of 150
nodes is simulated over a network area of size 2000m × 500m with
parameters listed in Simulation Table in stage-III and the number of
nodes forming the traffic are increased from 15 to 135 in the step of
30 and the simulation results obtained are presented in this section.

42
0
20
40
60
80
100
120
15 45 75 105 135
Number of sources
DSR, p = 300s CBRP, p = 300s
Packet delivery fraction as a function of Traffic sources in low and
high mobility scenarios.

Channel Utilization
43
0
2
4
6
8
10
12
14
16
15 45 75 105 135
Number of sources
DSR, p = 300s CBRP, p = 300s
Channel utilization as a function of Traffic sources in low and high
mobility scenarios.

0
1
2
3
4
5
6
7
8
9
10
15 45 75 105 135
Number of sources
DSR, p = 300s CBRP, p = 300s
44
Average end to end delay as a function of Traffic sources in low and

0
2
4
6
8
10
12
14
16
18
20
15 45 75 105 135
Number of sources
DSR, p = 300s CBRP, p = 300s
45
Normalized routing load as a function of Traffic sources in low and

Control Overhead
0
2
4
6
8
10
12
14
15 45 75 105 135
Millions
Number of sources
DSR, p = 300s CBRP, p = 300s
0
20
40
60
80
100
120
140
160
180
200
15 45 75 105 135
Thousands
Number of sources
DSR, p = 300s CBRP, p = 300s
46
Control Overhead load as a function of Traffic sources in low and

Influence of node density
47
In this section the results of the simulations carried out by varying
the number of nodes over the network area from 30 to 150 with two
different pause times are presented separately with 30% and 70% of
the nodes forming the traffic.

0
20
40
60
80
100
120
30 60 90 120 150
Number of nodes per sq. km
DSR, p = 300s CBRP, p = 300s
0
10
20
30
40
50
60
70
80
30 60 90 120 150
DSR, p = 300s CBRP, p = 300s
48
Packet delivery fraction as a function of number of nodes per sq. km. and
30%, 70% traffic sources.

Channel Utilization
0
2
4
6
8
10
12
14
16
30 60 90 120 150
DSR, p = 300s CBRP, p = 300s
0
2
4
6
8
10
12
14
16
18
20
30 60 90 120 150
DSR, p = 300s CBRP, p = 300s
49
Channel utilization as a function of number of nodes per sq. km. and

0
0.5
1
1.5
2
2.5
3
3.5
4
30 60 90 120 150
DSR, p = 300s CBRP, p = 300s
0
1
2
3
4
5
6
7
8
9
30 60 90 120 150
DSR, p = 300s CBRP, p = 300s
50
Average end to end delay as a function of number of nodes per sq. km. and

0
1
2
3
4
5
6
7
8
30 60 90 120 150
DSR, p = 300s CBRP, p = 300s
0
2
4
6
8
10
12
14
16
18
20
30 60 90 120 150
DSR, p = 300s CBRP, p = 300s
51
Normalized routing load as a function of number of nodes per sq. km. and

Control Overhead
0
10
20
30
40
50
60
70
80
90
30 60 90 120 150
Thousands
DSR, p = 300s CBRP, p = 300s
0
20
40
60
80
100
120
140
160
180
30 60 90 120 150
Thousands
DSR, p = 300s CBRP, p = 300s
0
1
2
3
4
5
6
7
30 60 90 120 150
Millions
DSR, p = 300s CBRP, p = 300s
0
2
4
6
8
10
12
14
30 60 90 120 150
Millions
Number of nodes per sq. kmControloverhead(bytes)
DSR, p = 300s CBRP, p = 300s
52
Control Overhead as a function of number of nodes per sq. km. and 30%,
70% traffic sources.

Conclusions
53
DSR has a lower PDF than CBRP in high mobility (0s pause time)
scenarios and more or less same PDF in stationary (300s pause
time) scenarios. In high mobility scenarios, the PDF due to 30%
traffic sources is better than that due to 70% traffic sources. The
performance degradation in PDF is due to packet drops by the
routing algorithm after being failed to transfer data in the active
routes. The packet drops are due to network partitioning, link break,
collision and congestion in the ad hoc network.

54
 CBRP has lower NRL than DSR in high mobility (0s pause time)
and a higher NRL in case of stationary (300s pause time) scenarios.
This is because CBRP only broadcasts route requests to cluster
heads. Gateway nodes receive the route requests as well but they
forward them to the next cluster-heads. This largely reduces the
route discovery packets which in turn reduces NRL. CBRP has a
better throughput than DSR in high mobility and stationary
scenarios with both traffic sources. This better throughput comes
from its cluster based structure which largely reduces network
traffic.
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cluster based routing protocol for ad hoc networks

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