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CHAPTER 6

SIMULATION AND RESULTS

For a sensor network to be useful, the location of each node must

be determined (Howard et al 2001 and Winfield et al 2000). Fortunately, it is

possible to determine the location of nodes in a network by conducting

suitable simulation experiments and evaluating their efficiency. Simulation

experiments are conducted aiming at evaluating the network lifetime and

energy efficiency of the deployment patterns with a suitable routing algorithm

and congestion control algorithm. Placement of sensor nodes play a very

important role on sensor networks (Howard et al 2001, Winfield et al 2000

and Bansal et al 2002). Based on the position of the sensor nodes the

efficiency of detecting the signal is improved (Clare et al 1999). Hence this

research analyses seven different distribution patterns of placing the nodes.

6.1 SIMULATION SETUP

The seven patterns shown in Figures 5.1 to 5.7 are simulated using

ns2. Initially, the distance covered by a sensor node is evaluated, considering

only two wireless nodes. With these nodes simulated as wireless nodes and by

varying the antenna height and transmitter power, the minimum required

antenna height and transmitter power required to cover a diagonal distance is

found for each pattern. This power differs slightly for each node.

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The various simulation parameters assumed are given below:

Channel : Wireless Channel

Propagation : Free Space

Network Interface Type : Wireless Physical Interface

Mac Type : Mac 802.11

Interface Queue Type : Drop Tail / Priority Queue

Antenna : Omni Antenna

Interface Queue Length : 50

Routing Protocol : AODV / DSDV/ DSR/ HETRA

Antenna Height : 0.35 m

With these parameters, the wireless sensor network is simulated

with the seven distribution patterns already discussed. In all the seven

scenario, the source node placed initially at (2, 2), is made mobile. It is

initially made to move towards the point (250, 200) and then towards (2, 500).

The base station node receives the information from the sensor nodes.

To analyze the energy efficiency and NLT of the wireless sensor

network, the different routing protocols are assumed. They are AODV,

DSDV, DSR and HETRA. Along with these routing protocols, five different

TCP variants are assumed in the source node. They are TCP/Tahoe,

TCP/Reno, MIMD-Poly, PIPD-Poly and TCP/Exp.

With the parameters mentioned, simulation is performed by

transmitting packets from source node to the base station node through the

sensor nodes. The simulation scenario generated the patterns which are stored

in a nam file. The nam display for one of the patterns is shown in Figure 6.1.

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Figure 6.1 Scenario generated by the simulation of Circular pattern

generated by the nam

6.2 SIMULATION RESULTS AND ANALYSIS

The simulation program may include the following statements to

generate the trace file.

set tracefd [open hetra.tr w]

The program used by ns2 to generate the trace is properly modified

that will include the details such as energy spent and the remaining energy

available after each transmission and reception. These trace files are properly

utilized to extract the energy remaining in the nodes after each transmission

and reception. The following AWK program performs this extraction.

set awkCode {

BEGIN { print "" >> "hetra1"; }

{if ($7 == "tcp" && $1 == "s" || $1 == "r")

{time = $2;

energy = $14*1;}

print time, energy >> "hetra1";}}

exec awk $awkCode hetra.tr

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The above program extracts the information from the trace file

generated (for example hetra.tr). The information extracted is the time

(in seconds) at which the source node or the intermediate node either

transmits ($1=s) or receives ($1=r) and the remaining energy (in Joules) in the

source node or the intermediate node. After extracting the necessary details

the energy versus time plot is drawn using the gnuplot program available in

linux.

The trace file of simulation experiments conducted with the seven

different distribution patterns (ALL, CIRCULAR, CROSS, DIAMOND and

EYE) with the four routing algorithms (AODV, DSDV, DSR and HETRA)

and five congestion control algorithms (TCP, Reno, MIMD, PIPD, Exp) are

used to find the NLT.

The values of NLTs extracted from the trace file of various

simulations are depicted in Figures 6.2 to 6.8. These figures give the variation

of energy from initial 0.5 Joules to zero Joules, in the duration of the NLT of

each simulated network configuration. Assuming the TCP/Exp congestion

control, Figure 6.2 give the values of NLT for AODV, DSDV, DSR and

HETRA routing protocols using the ALL node distribution pattern. Similarly

Figures 4.9 to 4.16 give the NLTs using the other four node distribution

patterns.

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(a) (b)

(c) (d)

Figure 6.2 Remaining Energy in nodes of WSN with ALL Pattern using

Various Routing Algorithms and TCP/Exp Congestion

Control

Energy versus Time Plot of DSR

En

erg

y i

n J

ou

les

Time in Seconds

Energy versus Time Plot of DSDV

Energy versus Time Plot of AODV Energy versus Time Plot of HETRA

En

erg

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Time in Seconds

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Time in Seconds Time in Seconds

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(a) (b)

(c) (d)

Figure 6.3 Remaining Energy in nodes of WSN with CIRCULAR

Pattern using Various Routing Algorithms and TCP/Exp

Congestion Control

.


En

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Time in Seconds



En

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(a) (b)

(c) (d)

Figure 6.4 Remaining Energy in nodes of WSN with CROSS Pattern

using Various Routing Algorithms and TCP/Exp Congestion

Control


En

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Time in Seconds



En

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Time in Seconds

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(a) (b)

(c) (d)

Figure 6.5 Remaining Energy in nodes of WSN with DIAMOND

Pattern using Various Routing Algorithms and TCP/Exp

Congestion Control


En

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Time in Seconds



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(a) (b)

(c) (d)

Figure 6.6 Remaining Energy in nodes of WSN with EYE Pattern using


Control


En

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Time in Seconds



En

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(a) (b)

(c) (d)

Figure 6.7 Remaining Energy in nodes of WSN with STEP Pattern

using Various Routing Algorithms and TCP/Exp Congestion

Control


En

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Time in Seconds



En

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(a) (b)

(c) (d)

Figure 6.8 Remaining Energy in nodes of WSN with CHI Pattern using


Control

The NLTs of each simulation for all node distribution patterns is

compared in Figure 6.9. This figure shows that the HETRA routing algorithm

increases the NLT. This increase is due to the strategy used to select the

nodes for transmission and reception based on the remaining node energy.

The routing from source to destination is also based on the HET constructed

using the above strategy. The exact values of NLT by assuming an initial

energy of 0.5 Jules are tabulated in Table 6.1 and the same is depicted in

Figure 6.9. The numbers of packets delivered by these are also tabulated in

Table 6.2 and they are compared in Figure 6.10.

Energy versus Time Plot of DSRE

ner

gy

in

Jo

ule

s

Time in Seconds



En

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Table 6.1 NLT of WSN with various Routing Algorithms and

TCP/Exp Congestion Control

NLT of various Routing AlgorithmsNode Distribution

Patterns DSR DSDV AODV HETRA

ALL 2.54 2.56 2.55 7.08

CIRCULAR 1.502 2.57 1.54 5.91

CROSS 1.36 2.69 1.42 5.83

DIAMOND 1.53 2.23 1.54 6.96

EYE 1.46 2.47 1.49 6.09

STEP 0.87 2.3 1.14 4.84

CHI SQUARE 1.14 1.18 0.97 4.53

NLT with TCP/Exp Congestion Control

0

1

2

3

4

5

6

7

8

ALL CIRCULAR CROSS DIAMOND EYE STEP CHI

SQUARE

Node Placement Patterns

Ne

two

rk L

ifeti

me i

n S

eco

nd

s

DSR

DSDV

AODV

HETRA

Figure 6.9 NLT of WSN with Various Routing Algorithms and

TCP/Exp Congestion Control

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Table 6.2 Number of Data Packets delivered in WSN with Various

Routing Algorithms and TCP/Exp Congestion Control

Number of Data packets of various Routing

AlgorithmsNode Distribution

PatternsDSR DSDV AODV HETRA

ALL 1712 1181 1739 1721

CIRCULAR 1705 1687 1713 1710

CROSS 1720 721 1731 1722

DIAMOND 1728 1480 1718 1717

EYE 1733 660 1715 1715

STEP 1511 763 1504 1507

CHI SQUARE 1741 1134 1717 1715

Data Packets Received with TCP/Exp Congestion Control

0

200

400

600

800

1000

1200

1400

1600

1800

2000


SQUARE


No

. o

f D

ata

Packets

DSR

DSDV

AODV

HETRA

Figure 6.10 Number Data Packets delivered in WSN with various

Routing Algorithms and TCP/Exp Congestion Control

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This shows that the combination HETRA with TCP/Exp performs

better. This combination has higher energy efficiency and also throughput.

Hence, the NLT of WSN with HETRA/Exp combination has improved the

overall efficiency of the network. As the number of nodes in CROSS pattern

is less compared with other patterns and the energy efficiency is comparable

with other patterns, the CROSS pattern is the most energy efficient pattern

among the seven fixed patterns assumed.

6.3 DANLT PRODUCT – PERFORMANCE METRIC USED FOR

COMPARISON

For comparing the performance of different distribution patterns, a

common parameter is formulated. To arrive at a common parameter, initially

ANLT per node is calculated as given below:

Average network lifetime per node = NLT/Number of nodes (6.1)

This ANLT is calculated for all the simulated patterns. The result

shows that the value is maximum for CROSS pattern. Hence, among the

seven patterns assumed, CROSS pattern with HETRA and TCP/Exp is the

most efficient combination.

Based on the number of data packets delivered and NLT, a new

parameter is formulated to compare the performance of WSN with the

different node placement patterns, routing algorithms and congestion control

algorithms. The parameter is named as Data packets–ANLT product and is

evaluated as given below:

Data packets–ANLT product = Number of Data packets delivered * ANLT

(6.2)

This parameter gives an effective way of comparing the combined

performance of energy efficiency, throughput, Network lifetime and number

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of nodes in each distribution pattern of WSN. This parameter is very useful

in the comparison of the seven node distribution patterns assumed.

The NLT of the seven patterns (for TCP/Exp congestion control) is

shown in Figure 6.9. This shows that the NLT of WSN with HETRA and

Exp combination is the highest among the four routing algorithms assumed.

Among the patterns, ALL pattern has the highest NLT of 7.08 seconds. The

number of data packets delivered is compared for the seven patterns (with

TCP/Exp) in Figure 6.10. This figure clearly indicates that the number of data

packets delivered is the maximum for the combination of HETRA with

TCP/Exp in cross pattern.

DANLT product is evaluated for combining the NLT and the

number of data packets into a single measure for comparison. This measure

will clearly indicate the most efficient pattern among the seven patterns. This

comparison is depicted in Figure 6.11. This figure clearly indicates that the

DANLT product is the maximum for the combination HETRA with TCP/Exp

in CROSS pattern. Hence this combination proves to be the most efficient in

terms of total energy spent, number of data packets delivered and Network

lifetime.

Similarly in CROSS pattern the five different congestion control

schemes are assumed and simulation is performed to compare the congestion

control algorithm that best suites the WSN. Again the NLT for various

congestion control schemes and routing algorithms are evaluated for the cross

pattern from the trace file. The results are plotted in Figure 6.12. Number of

data packets delivered for the same combination of CROSS/HETRA with

different congestion control schemes are also found from the simulation trace

files and are shown in Figure 6.13. The DANLT product is evaluated and is

shown in Figure 6.14. This parameter indicates that the combination of

CROSS pattern with HETRA and TCP/Exp is the most efficient among all the

patterns.

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DANLT Product with TCP/Exp Congestion Control

0

100

200

300

400

500

600


SQUARE


DA

NL

T P

rod

uc

t

DSR

DSDV

AODV

HETRA

Figure 6.11 DANLT product of WSN with various Routing Algorithms

and TCP/Exp Congestion Control

Network Lifetime (NLT) of WSN with various Congestion Control

0

1

2

3

4

5

6

7

TCP Exp Reno MIMD PIPD

Congestion Control Algorithms

NL

T in

Se

cs

.

DSR

DSDV

AODV

HETRA

Figure 6.12 NLT of WSN CROSS Pattern with various Routing and


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Number of Data Packets delivered in WSN with various Congestion Control

0

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400

600

800

1000

1200

1400

1600

1800

2000



Nu

mb

er

of

Da

ta P

ac

ke

ts d

eli

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red

DSR

DSDV

AODV

HETRA

Figure 6.13 Number of Data Packets delivered in WSN CROSS Pattern

with various Routing and Congestion Control Algorithms

DANLT Product of WSN with various Congestion Control

0

100

200

300

400

500

600



DA

NL

T P

rod

uct

DSR

DSDV

AODV

HETRA

Figure 6.14 DANLT Product of WSN CROSS Pattern with various

Routing and Congestion Control Algorithms

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In this section, the NLT of WSN with different node distribution

patterns are analysed with the combination of routing algorithms and

congestion control algorithms. Seven node distribution patterns – ALL,

CIRCULAR, CROSS, DIAMOND, STEP, CHI SQUARE and EYE four

routing algorithms – DSDV, AODV, DSR, and HETRA and five TCP

congestion control schemes- TCP, Reno, MIMD, PIPD and Exp are assumed.

Among these, HETRA and Tcp/Exp are the proposed routing algorithm and

congestion control algorithm respectively.

Simulations are performed in ns2 with HETRA/Exp and TCP/Exp

implemented in it. The results of simulation are used for the analysis. The

trace files generated by the simulation experiments are used to evaluate the

parameters such as NLT, ANLT, Data packets delivered and DANLT

product. The NLT of each simulation with TCP/Exp congestion control

algorithm, Four Routing Protocols and Seven node distribution patterns are

shown in Figures 5.1 to 5.7. These parameters are compared in Figures 6.2

to 6.8.

The results clearly indicate that the WSN with the nodes

distributed in the pattern of CROSS with the routing algorithm as HETRA

and congestion control as TCP/Exp, performs most efficiently in terms of the

energy consumption , NLT and throughput.

6.4 PERFORMANCE EVALUATION OF HETRA WITH

TCP/Exp IN WIRELESS SENSOR NETWORK

INTERFACED TO A WIRED TCP/IP NETWORK

WSN is used to solve many critical real life situations and it

provides a very good solutions. Earth quake detection and intelligent

agriculture are two such applications. In many of such applications, data

sensed and collected by WSN needs to be processed further and transported to

servers where the end results are to be analyzed and utilized. For such

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situations, the data collecting centre (base station node), needs to

communicate the data collected to the end user with the available network.

Since ubiquitous wired networking (i.e. Internet) is available, the base stations

need to transfer the data through these wired networks. For each application

the base station node needs to be interfaced to a wired TCP/IP network

(Dunkels et al 2004). This chapter evaluates the performance of the proposed

algorithms in such an integrated network of WSN interfaced to a wired

TCP/IP network.

6.4.1 Wired Cum Wireless Sensor Networks

This section explains about the simulations conducted to evaluate

the performance of the proposed routing and congestion control algorithms

HETRA and TCP/Exp in the seven node distribution patterns discussed in the

previous chapter. The details of hierarchical addressing used for interfacing

the WSN to the wired TCP/IP network in ns2 are also explained in detail.

Performance of the HETRA and TCP/Exp is evaluated by assuming

a wireless sensor network interfaced to a wired network as shown in

Figure 6.15.

Figure 6.15 WSN interfaced to wired network (Internet)

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This work is done to establish the following:

The TCP/Exp algorithm is designed for wired network and is

found to perform extremely good in such networks when

compared to the other standard TCP congestion control

algorithms.

HETRA is designed for optimized use of energy and extend

the NLT of WSN. This algorithm also performs very well

compared with the other wireless routing algorithms.

The Combination HETRA and TCP/Exp performs better in

almost all fixed pattern topology of WSN.

Hence, this combination will definitely perform better if a network

topology is created with the wireless sensor network nodes and sink being

connected to a wired network. To justify this, a wireless cum wired topology

is simulated and the performance of the combination HETRA with TCP/Exp

is evaluated.

6.4.2 Node Distribution Pattern for WSN with Wired Interface

The Wireless network remains the same as explained in the

previous chapter and the seven proposed node distributions patterns are used.

The WSN topology uses a central base station node to collect the sensed data.

The wired TCP/IP network is interfaced to such WSN network.

The base station node is connected to a router node and this router in turn is

connected to two sink nodes. Figure 6.16 shows one simulated topology

(ALL Pattern) with the wired network. The wired network may be connected

to any existing wired TCP/IP network.

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Figure 6.16 Nodes placed as rectangular grid (Pattern - ALL)

6.4.3 Simulation of WSN with Wired Interface

The topologies simulated are the same seven node distribution

patterns used in chapter 5. But a wired network containing a router node

and two sink nodes are interfaced to the base station node of WSN, which

receives the data packets from the sensor nodes. The topologies simulated are

explained below.

In addition to the simulation set up discussed in chapter 3 for

simulating the WSN, additional nodes are added for forming a wired network.

Here, all the wireless nodes and nodes in the wired network are allotted with

hierarchical addressing. The hierarchical addressing in ns2 uses the following

format.

Domain_address. Cluster_address. Node_address.

The nodes are divided into two domains - one containing wireless

nodes including the base station node, the other containing nodes of wired

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network. The interface between WSN and Wired network is through the base

station node. The data sensed by the sensor nodes are sent to the base station

node through the intermediate sensor nodes. These data received by the base

station node from the various sensor nodes are collected and locally

processed. The information processed is sent to the end user through the

wired TCP/IP network, by sending them first to the gateway (router) node and

then to the required sink node(end user).

The query-response makes use of the hierarchical addresses while

sending a query to the sensor node as well as while transmitting the response

(after sensing the required data) to the end user.

6.4.4 Simulation Program

In ns2, simulation of Hierarchical Addressing is possible only with

AODV and DSDV among the wireless routing protocols available. This is

because these protocols include both domain/clustering support and base

station support. But DSR in ns2 is implemented as a flat routing protocol

only. It does not provide domain/clustering support and base station support.

The proposed HETRA algorithm includes the domain/clustering support and

base station support. Hence the performance evaluation of WSN with wired

network interface compares HETRA with AODV and DSDV only.

The program segment used to define the hierarchical addressing

space is given below:

AddrParams set domain_num_ 2

AddrParams set cluster_num_ {1 1}

AddrParams set nodes_num_ {3 51}

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As already explained, the entire network nodes are grouped into

two domains. Each domain consists of a single cluster. Each cluster consists

of the nodes. Cluster 0 in domain 0 consists of nodes of wired network, i.e.

one router and two host nodes. Cluster 0 in domain 1 consists of all the

wireless sensor nodes. In addition, this cluster also includes the gateway node

which acts as the interface node between the wireless network and wired

network. Based on these assignments of domain and cluster, each node is

allotted with the IP address as given in the program segment.

set router1 [$ns node 0.0.0]

set host1 [$ns node 0.0.1]

set host2 [$ns node 0.0.2]

set gw1 [$ns node 1.0.0]

set temp {1.0.1 1.0.2 1.0.3 1.0.4 1.0.5 1.0.6 1.0.7 1.0.8 1.0.9 1.0.10 1.0.11

1.0.12 1.0.13 1.0.14 1.0.15 1.0.16 1.0.17 1.0.18 1.0.19 1.0.20 1.0.21 1.0.22

1.0.23 1.0.24 1.0.25 1.0.26 1.0.27 1.0.28 1.0.29 1.0.30 1.0.31 1.0.32 1.0.33

1.0.34 1.0.35 1.0.36 1.0.37 1.0.38 1.0.39 1.0.40 1.0.41 1.0.42 1.0.43 1.0.44

1.0.45 1.0.46 1.0.47 1.0.48 1.0.49 1.0.50}

for {set i 4} {$i < $opt(wirelessNodes)+3 } {incr i} {

set mobile$i [$ns node [lindex $temp [expr $i-4]]]

}

6.5 SIMULATION OF NODE DISTRIBUTION PATTERNS FOR

WSN INTERFACED TO A WIRED TCP/IP NETWORK

Seven node distribution patterns are simulated for evaluating the

performance of the combination of the proposed Routing Algorithm and

Congestion Control Algorithm- HETRA and TCP/Exp. These topologies are

simulated to cover a rectangular area of 800m 500m. This area can be

changed to any size by modifying the size in the tcl program. The simulation

setup for each node distribution patterns is discussed below.

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6.5.1 ALL Pattern

This pattern shown in Figure 6.17 covers the area by placing a

rectangular grid of sensor nodes. Totally 50 nodes are placed as a 5 10

rectangular array. One node is assumed to be the phenomenon node. This

node is made to move over the entire area during the simulation period, with

the assumption of a phenomenon occurring at different places of the area.

This phenomenon node sends signal to the sensor nodes, which is analogous

to the sensor nodes sensing the phenomenon. With this basic assumption, the

sensor nodes after sensing the phenomenon send the information to a central

node placed at the location (250, 150).

Figure 6.17 Nodes placed as rectangular grid (Pattern - ALL)

This central node is the gateway node or base station node. The

data collected by this gateway node is sent over the wired network. The wired

network is now formed by connecting a router to the gateway node and two

hosts (or destination nodes) connected to the router nodes. The gateway node

sends the data through the router node to the host node, where the data is

processed.

In the case of simulation of WSN interfaced to wired TCP/IP

network, hierarchical addressing is used. This is analogous to the allocation

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of IP address to each node including the sensor nodes. This facilitates the

gateway node to act as wireless node to collect the sensed data and as a wired

node to communicate on wired TCP/IP network.

The hierarchical addressing in ns2 uses the following format of

addressing, Domain-address. Cluster-address. Node-address.

Here in the simulated topology, two domains are assumed. Each

domain is assumed with one cluster each. One cluster consists of sensor

nodes and gateway node and the other cluster consists of router node and host

nodes of wired network.

In ALL pattern the hierarchical addressing for the router and host

nodes are allocated as shown below:

Router {0.0.0} - node 0

Host 1 {0.0.1} - node 1

Host 2 {0.0.2} - node 2

The address for the wireless sensor nodes are:

Gateway {1.0.0} - node 3

Sensor nodes {1.0.1} TO {1.0.50} - node 4 to 53

With these address allocations, a wireless and wired network

topology is simulated.

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6.5.2 CIRCULAR Pattern

This pattern covers the area with 42 nodes placed in a CIRCULAR

pattern as shown in Figure 6.18. The gateway node is placed at the location

(250, 250). Here again the phenomena node is made to move around the area

simulating the conditions of occurrence of a natural phenomenon.

Figure 6.18 Nodes placed as a circular pattern (Pattern - CIRCULAR)

The hierarchical addresses of the wired network nodes i.e. router

and host nodes are the same. The gateway node also has the same address as

that allocated in the case of ALL pattern. The sensor node addresses are from

{1.0.1} to {1.0.42}.

6.5.3 DIAMOND Pattern

The sensor nodes are arranged in the form of a DIAMOND pattern

as shown in Figure 6.19 to cover the area. Here 37 sensor nodes are simulated

and the gateway node is placed at (250, 250).

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Except the sensor nodes, other nodes have allocated with the same

hierarchical address. The sensor nodes have the addresses ranging from

{1.0.1} to {1.0.37}

Figure 6.19 Nodes placed in a diamond pattern (Pattern - DIAMOND)

6.5.4 CROSS Pattern

This pattern covers the area with 20 nodes placed in a CROSS

pattern. This is shown in Figure 6.20. The gateway node is placed at the

location (300, 150). Here again the phenomena node is made to move around

the area simulating the conditions of occurrence of a natural phenomenon.

Figure 6.20 Nodes placed in a cross pattern (Pattern - CROSS)

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and host nodes are the same. The gateway node also has the same address.

The sensor node addresses are ranging from {1.0.1} to {1.0.20}

6.5.5 CHI SQUARE Distribution Pattern

This pattern covers the area with 24 nodes placed in a CHI

SQUARE distribution pattern as shown in Figure 6.21. The gateway node is

placed at the location (164, 92). Here again the phenomena node is made to

move around the area simulating the conditions of occurrence of a natural

phenomenon.

Figure 6.21 Nodes placed in a Chi Square Distribution pattern

(Pattern - CHI)



The sensor node addresses are from {1.0.1} to {1.0.24}.

6.5.6 STEP Pattern

The pattern shown in Figure 6.22 covers the area with 19 nodes

placed in a STEP pattern. The gateway node is placed at the location

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The sensor node addresses are from {1.0.1} to {1.0.19}

Figure 6.22 Nodes placed in a STEP pattern (Pattern - STEP)

6.5.7 EYE Pattern

This pattern covers the area with 33 nodes placed in an EYE pattern

as shown in Figure 6.23. The gateway node is placed at the location





The sensor node addresses are from {1.0.1} to {1.0.33}.

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Figure 6.23 Nodes placed in an eye pattern (Pattern - EYE)

With these simulated node distribution patterns for the WSN

interfaced to wired network, the network is simulated with the various routing

algorithms and congestion control algorithms. The performance of these

algorithms is measured using the same metric used for the WSN with only

wireless nodes. The number of data packets delivered and the resulting

throughput are evaluated. Then the NLT, ANLT and DANLT product terms

are evaluated for comparison. The next section discusses the results of the

simulation experiments conducted.

6.6 RESULTS AND ANALYSIS OF THE SIMULATION OF

WSN WITH WIRED INTERFACE

The simulation experiments with the routing algorithms (AODV,

DSDV and HETRA), Congestion control algorithms (TCP/Tahoe, TCP/Reno,

MIMD-Poly, PIPD-Poly and TCP/Exp) with different node distribution

patterns are conducted using the tcl program and hierarchical addressing. The

results of the experiments are tabulated and also shown in graphs.

The simulation is performed for two different time duration. One

simulation is conducted for 10 seconds and the other is for 20 seconds.

Simulation is performed by choosing a congestion control algorithm, a

154

routing protocol and a node distribution pattern. The different routing

protocols assumed are AODV, DSDV, and HETRA. The congestion control

algorithms assumed are TCP/Tahoe, Reno, MIMD-Poly, PIPD-Poly and

TCP/Exp. The topologies simulated are wired interface with ALL pattern,

CROSS pattern, CIRCULAR Pattern, DIAMOND pattern, EYE pattern,

STEP pattern and CHI SQUARE Distribution pattern.

For example, the combination of AODV with TCP/Tahoe is

initially assumed in the ALL pattern. Simulation assumes that different

sensor nodes senses the data and send them to the base station node. The base

station node which is also the gateway node collects all the data for an

interval of time and sends them over the wired network. These data through

the router travels to the host node which is assumed to be the server node

when further processing is to be done.

In the simulation experiments, instead of all the sensor nodes

assumed to sense and transmit the data to the base station node, a sample of

four sensor nodes are assumed to transmit the sensed data. These nodes are

assumed to be in four different directions from the central base station node.

The base station node is assumed to collect these data for a fixed

interval of time and send all these collected data over the wired network.

Each simulation experiment conducted will store the details of

simulation in two files: a trace file and a nam file. The nam file is used to

visually show the various activities during the entire simulation period. The

packets traveling from the source node to the destination node through the

intermediate nodes, the dropped packets, the acknowledgement packets from

the destination node to the source node will be visually shown by running the

nam file in the nam editor.

155

The trace file in turn records all these events shown visually by a

nam, in the form of records. Each record gives the following details:

Packet is sent or received

Time at which the packet is sent or received

The packet is a TCP packet, TCP/ACK packet or RTR packet

id of the source node and intermediate nodes

port address

By extracting the information from their trace file, the last

successfully acknowledged data can be formed. Using this information, the

number of data packets successfully received at the base station node can be

evaluated. By using the equation (3.8) the throughput can also be evaluated.

The simulation experiment is now repeated for AODV with

TCP/Reno, MIMD, PIPD and TCP/Exp in ALL pattern. In each case, the

number of data packets successfully received and the corresponding

throughput is found and tabulated.

Similarly, the simulation experiment is repeated with DSDV and all

the congestion control algorithms in ALL pattern. The same experiment is

repeated for HETRA with all congestion control algorithms in ALL pattern.

In each case, the number of data packets successfully received at

the gateway node and the corresponding throughput is evaluated. These

values are presented in Figure 6.24.

156

Figure 6.24 Number of Data Packets received and Throughput in ALL

Pattern

This figure clearly shows that the HETRA routing algorithm

performs better than AODV and DSDV. With HETRA as the routing

algorithm, TCP/Exp produces better results with less number of packet drops

and higher throughput compared with other congestion control algorithms i.e.

TCP/Reno, MIMD, PIPD, TCP/Tahoe.

Hence, the combination HETRA and TCP/Exp perform more

efficiently in ALL pattern compared with other combination of Routing and

congestion control algorithms.

The above simulation experiment is repeated for the patterns,

CROSS, CIRCULAR, DIAMOND, EYE, STEP and CHI SQUARE

Distribtution.

The number of data packets successfully received at the base

station node and the corresponding throughput values are found. These

values are shown in Figures 6.25 to 6.30. All these figures clearly indicate

that in each pattern the combination HETRA performs better compared with

AODV and DSDV with HETRA as the routing algorithm, TCP/Exp

congestion control algorithm produces better results compared with

TCP/Tahoe, Reno, MIMD and PIPD.

157

Figure 6.25 Number of Data Packets received and Throughput in

CIRCULAR Pattern


CROSS Pattern


DIAMOND Pattern

158

Figure 6.28 Number of Data Packets received and Throughput in EYE

Pattern

Figure 6.29 Number of Data Packets received and Throughput in STEP

Pattern

Figure 6.30 Number of Data Packets received and Throughput in CHI

SQUARE Pattern

159

When the result of the combination HETRA and EXP is compared

with the different patterns, CROSS pattern delivers the maximum of

1253 packets in a simulation time of 10 seconds. Next to CROSS pattern,

ALL pattern delivers 1224 packets. But the number of sensor nodes in

CROSS pattern is 20 and in ALL pattern it is 50. Hence the CROSS pattern

is more efficient than the other patterns. Hence, the combination HETRA,

TCP/Exp and CROSS distribution pattern performs most efficiently among

the combinations simulated.

The comparisons of congestion control TCP/Exp with all the

routing algorithms and node distribution patterns is shown in Figure 6.31.

This clearly indicates that the combination HETRA, TCP/Exp and CROSS

pattern is the best choice.

Figure 6.31 Comparisons of TCP/Exp with all the routing algorithms

and node distribution patterns

160

The simulation experiment is repeated for a simulation time of

20 seconds. The same combinations are simulated. These results again prove

that the same combination is the most efficient among all the simulated

combinations.

Simulation experiments are exclusively conducted to evaluate the

energy efficiency of the various combinations of Routing algorithms (AODV,

DSDV and HETRA), congestion control Algorithms (TCP/Tahoe, Reno,

MIMD, PIPD and TCP/Exp) in the seven node distribution patterns (ALL,

CIRCULAR, CROSS, DIAMOND, STEP, EYE AND CHI SQUARE). An

initial energy of 0.5 Joules is assumed in each simulation.

Lifetime of the network is calculated for each simulated network

topology from the trace file. The lifetime of the network is taken as the time

duration from the first packet that is transmitted from a node and the last

packet (before a single node dies out of energy) received at the base station

node. This value is calculated by extracting the information of time instead of

packet transmission/reception and the energy remaining in each node from the

trace file using the awk programming discussed in chapter 5.

From this extracted information, the network lifetime is calculated

and the values are shown for each pattern in the Figures 6.32 (a) to (g). From

these figure we could infer that HETRA, yielding a maximum network

lifetime in each pattern and EXP give better results among the congestion

control algorithm. Hence, in WSN with wired interface, the combination

HETRA with EXP in CROSS pattern yielded the maximum in terms of

throughput as well as NLT.

Again, as a single parameter for comparison of the performance,

the DANLT product is evaluated and is shown in Figure 6.33 (a) through (g)

for all the patterns. This again shows that, the only combination which is

more energy efficient among all the simulated combinations is HETRA,

TCP/Exp in CROSS pattern.

161

0

1

2

3

4

5

6

7

Reno TCP M IM D PIPD EXP


NLT

in

se

co

nd

s

AODV

DSDV

HETRA

0

1

2

3

4

5

6



NLT

in

se

co

nd

s

AODV

DSDV

HETRA

(a) ALL Pattern (b) CIRCULAR Pattern

0

2

4

6

8



NLT

in

se

co

nd

s

AODV

DSDV

HETRA 0

1

2

3

4

5

6



NLT

in

se

co

nd

s

AODV

DSDV

HETRA

(c) CROSS Pattern (d) DIAMOND Pattern

0

0.5

1

1.5

2

2.5

3

3.5



NLT

in

se

co

nd

s

AODV

DSDV

HETRA

0

1

2

3

4

5

6

Reno TCP MIMD PIPD EXP

Congestion Control Algorithm

NL

T i

n s

eco

nd

s

AODV

DSDV

HETRA

(e) EYE Pattern (f) STEP Pattern

0

1

2

3

4

5

6


Congestion Control Algorithm

NL

T in

seco

nd

s

AODV

DSDV

HETRA

(g) CHI SQUARE Distribution Pattern

Figure 6.32 NLT of different node distribution patterns

162

0

50

100

150



DA

NLT

Pro

du

ct

AODV

DSDV

HETRA 0

20

40

60

80

100

120

140



DA

NLT

Pro

du

ct

AODV

DSDV

HETRA

(a) ALL Pattern (b) CIRCULAR Pattern

0

100

200

300

400

500



DA

NLT

Pro

du

ct

AODV

DSDV

HETRA

0

20

40

60

80

100

120

140



DA

NLT

Pro

du

ct

AODV

DSDV

HETRA

(c) CROSS Pattern (d) DIAMOND Pattern

0

20

40

60

80

100



DA

NLT

Pro

du

ct

AODV

DSDV

HETRA

0

100

200

300

400

Reno TCP MIMDPIPD EXP

Congestion Control

Algorithms

DA

NL

T P

rod

uc

t

AODV

DSDV

HETRA

(e) EYE Pattern (f) STEP Pattern

0

50

100

150

200

250



DA

NL

T p

rod

uc

t

AODV

DSDV

HETRA

(g) CHI SQUARE Distribution Pattern

Figure 6.33 DANLT Product of Different Node Distribution Patterns

163

6.7 COMPARISON OF THEORETICAL VALUES OF NLT

WITH THE SIMULATED RESULTS

The maximum theoretical value of NLT may be calculated from the

equation (5.17) by substituting the values of initial energy, energy consumed

for transmission, reception and processing and the number of nodes of each

pattern. The NLTmax for each pattern may be calculated and compared with

the NLTs obtained by conducting the simulation experiments using ns2. The

NLTmax is now calculated for the reference pattern ‘ALL’.

6.7.1 Calculation of NLTmax for ALL Pattern

The values used for the simulation experiments conducted to find

the NLT are used and substituted in equation (5.17).

These values are,

Initial energy Ei = 0.5 Joules or 0.5 watt-seconds

(1 Joule = 2.778 10-7 KWh)

Energy consumed for transmitting the data, et = 0.08w

Energy consumed for receiving the data, er = 0.02w

Energy consumed for sensing and processing the data, ep= 0 w.

Compared to the values of energy consumed for transmission and

reception, the consumption of energy for sensing the phenomenon and

internal processing in the sensor node will be very negligible and hence

assumed as 0 w.

164

The probability of the two nodes involved sensing and transmitting

data to the base station is obtained by substituting x=2 in f(x), the weighting

function. Hence,

f(x) = 2 * 2

2

2

1x

e

= 0.108

navg is the average number of nodes involved in the transmission of data from

the source to the base station and this value for the all pattern is

approximately 5.

The number of nodes in ALL pattern is 50. Hence the cost factor

topo is calculated as,

topo =ALL

p

N

N

= 1 ( since Np = NALL)

Substituting all these values in equation for NLTmax

2

pimax

xALL

2t r p avg

NENLT *

N1(e e e )* 2* e *n

2

0.5*1

(0.08 0.02)*0.108*5

= 9.259 seconds.

This value is the theoretical maximum of the NLT for ALL pattern.

Similarly, the value of NLTmax may be calculated for other patterns. The

values obtained are shown in Table 6.3.

165

Table 6.3 Values of NLTmax for the node placement patterns

Sl.No.Node Placement

Pattern

Number of

nodestopo NLTmax in

seconds

1. ALL 50 1 9.259

2. CHI Square 21 0.648 6.0

3. CIRCULAR 42 0.84 7.78

4. CROSS 20 0.632 5.86

5. DIAMOND 37 0.86 7.96

6. EYE 33 0.81 7.52

7. STEP 20 0.632 7.78

Now the theoretical values obtained above are compared with the

experimental values obtained by the simulation of the above patterns.

Table 6.4 shows this comparison for the various routing algorithms and

various congestion control algorithms for ALL Pattern.

Table 6.4 Comparison of Theoretical and Experimental NLT with

various Routing algorithms and congestion control

algorithms for ALL Pattern

Experimental value of NLT (in seconds) for

Routing Algorithms

Congestion

Control

Algorithms DSR DSDV AODV HETRA

Theoretical

NLTmax

(in seconds)

TCP 1.57 2.54 1.65 5.8

Exp 2.54 2.56 2.55 7.08

Reno 1.58 2.6 2.62 3

MIMD 1.54 2.55 1.56 4.5

PIPD 1.51 2.54 1.51 5.55

9.259

166

The comparison shows that the experimental value of NLT for

HETRA with TCP/Exp and TCP/Tahoe are closer to the theoretical

maximum. The values obtained with the other routing algorithms in

combination with the congestion control algorithms are less than the

theoretical maximum. The reason for this reduction in NLT is due to the fact

that the other routing algorithms do not consider the energy constraint while

forming the routing. Hence, routes formed with the aim of less number of

hops use almost the same set of intermediate nodes for transmission of sensed

data from a particular position of sensing field. This will exhaust the energy in

the intermediate nodes and lead to early network splitting.

A similar comparison may be presented for the other node

placement patterns. These are shown in Tables 6.5 to 6.10.



algorithms for CHI Pattern


Routing Algorithms

Congestion

Control


Theoretical

NLTmax

(in seconds)

TCP 1.09 1.87 0.91 3.747

Exp 1.14 1.18 0.97 4.53

Reno 1.03 1.87 0.94 2.02

MIMD 1.04 1.87 0.93 3.75

PIPD 1 1.85 0.96 3.81

6.0

167



algorithms for CIRCULAR Pattern


Routing Algorithms

Congestion

Control


Theoretical

NLTmax

(in seconds)

TCP 1.52 1.9 1.54 4.93

Exp 1.502 2.57 1.54 5.91

Reno 1.52 2.6 1.56 2.06

MIMD 1.522 2.57 1.527 3.9

PIPD 1.51 2.55 1.55 4.27

7.78



algorithms for CROSS Pattern


Routing Algorithms

Congestion

Control


Theoretical

NLTmax

(in seconds)

TCP 1.38 2.92 1.41 3.84

Exp 1.36 2.69 1.42 5.83

Reno 1.93 2.89 2.42 3

MIMD 1.36 2.91 1.39 3.58

PIPD 1.39 2.92 1.4 4.54

5.86

168



algorithms for DIAMOND Pattern


Routing Algorithms

Congestion

Control


Theoretical

NLTmax

(in seconds)

TCP 1.52 2.17 1.55 5.97

Exp 1.53 2.23 1.54 6.96

Reno 1.53 2.3 1.55 3.07

MIMD 1.53 2.22 1.55 3.96

PIPD 1.52 2.18 1.5 4.74

7.96



algorithms for EYE Pattern


Routing Algorithms

Congestion

Control


Theoretical

NLTmax

(in seconds)

TCP 1.47 3.06 1.48 5.09

Exp 1.46 2.47 1.49 6.09

Reno 1.47 2.92 2.44 2.06

MIMD 1.454 3.07 1.48 3.09

PIPD 1.45 3.07 1.49 4.08

7.52

169



algorithms for STEP Pattern


Routing Algorithms

Congestion

Control


Theoretical

NLTmax

(in seconds)

TCP 0.79 2.27 1 3.44

Exp 0.87 2.3 1.14 4.84

Reno 0.84 2.16 0.98 1.39

MIMD 0.87 2.21 0.98 2.41

PIPD 0.79 2.18 0.95 3.32

5.86

All the above comparisons show that the combinations HETRA

with TCP/Exp have the experimental values closely matching the theoretical

values.

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