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CHAPTER 5
LOCATION AIDED ENERGY EFFICIENT ROUTING
PROTOCOL
In this chapter an energy efficient routing protocol named
Location Aided Energy Efficient Routing (LAEER) for wireless sensor
network is proposed. The design of the proposed LAEER protocol is
explained in section 5.1. Simulation results of the proposed LAEER
protocol is discussed in section 5.2. The real-time implementation of the
proposed LAEER protocol is presented in section 5.3.
Consider a scalable wireless sensor network with M nodes that
are deployed in a n X n terrain. The location and energy information of
these M nodes are given below
T
1 2 3 M
T
1 2 3 M
T
1 2 3 M
X = x ,x ,x , ……….x
Y = y ,y ,y , .……….y
E = e ,e ,e , ...……….e
(5.1)
The deployed M nodes are categorized as source, destination and
relay nodes. The source and destination nodes are termed as non-
forwarding nodes and the relay nodes are referred to as forwarding nodes.
In the proposed LAEER protocol, the Routing metric (R) is a
function of PRR, V and Erem of the node’s battery which is given as
R = fn {PRR, V, Erem} (5.2)
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5.1 PROPOSED LOCATION AIDED ENERGY EFFICIENT
ROUTING (LAEER) PROTOCOL
The proposed Location Aided Energy Efficient Routing
(LAEER) protocol consists of four main functional modules. These
modules coordinate with each other to perform the task of multi-hop
routing for WSN. The architecture of the proposed protocol is illustrated in
Figure 5.1.
The modules are
1. Localization Engine
2. Neighborhood Management
3. Routing Management
4. Energy Management
Figure 5.1 Architecture of the proposed LAEER protocol
The flow chart describing the proposed LAEER protocol is given
in Figure 5.4.
Neighborhood Management
Localization Engine Energy Management
Routing Management
74
Various modules used in this protocol are explained below:
5.1.1 Localization Engine
The proposed LAEER protocol possesses a Localization Engine
module that determines the location of the nodes. Either the traditional
GPS based location finding algorithms or any alternative algorithm like the
one proposed in chapter 3 can be used based on the environment. The
environment can be either indoor or outdoor. The proposed LAEER
protocol uses the location information of the nodes as described in
Chapter 3.
5.1.2 Neighborhood Management
Neighborhood Management consists of the neighbor discovery
module which is triggered when the Neighbor Table (NT) is found empty.
Initially, the source node broadcasts the Request To Route (RTR) packet
and waits for a reply from its neighbor nodes. In order to minimize the
communication overhead involved in neighbor discovery process, the reply
to RTR is restricted within the forwarding neighbor nodes as shown in
Figure 5.2. To determine whether the neighboring nodes are forwarding
nodes, each node computes the progress distance calculation using the
following relation.
Pd = d(N, D) < d(S, D) (5.3)
where, Pd = progress distance in meters
N = neighboring node
S = source node
D = destination node (sink)
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d(N, D) = distance between the neighboring node and
destination node
d(S, D) = distance between the source node and destination
node
Figure 5.2 Route reply packet from forwarding neighbor nodes
The nodes which satisfy the above condition are considered as
forwarding nodes with their forward flag (ff) set to 1. The reply packet
consists of node ID, residual energy, forward flag, and location
information, transmit time of RTR request. Neighbor Table (NT) is
constructed in the source node with the information obtained from the
reply packet. The RTR request format is shown in Table 5.1.
Table 5.1 Format of the Request to Route (RTR) packet
Node
IDX axis Y axis
Residual
Energy
Sequence
Number
Transmit
time
2 byte 2 byte 2 byte 2 byte 2 byte 2 byte
The number of entries in NT is based on node memory size. The
timeout value of the packet depends on LAEER protocol. This value will
be restarted upon every acknowledgement of data at MAC level. To avoid
D
S
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the periodic beaconing process and to maintain the updated energy value of
the neighbors, residual energy updates are performed only at selected
thresholds such as 66%, 33%, 10% of the initial or maximum energy
assigned to that node. The reduction in frequent updates preserves the
impact on performance parameters.
5.1.3 Routing Management
The Routing Management module is the core of the proposed
LAEER protocol, in which the optimal forwarding neighbor node selection
from NT is performed. If NT is found empty, then Neighborhood
Management module is invoked to construct NT. The Optimal Forwarding
(OF) neighbor node is selected based on the highest weighted value in
terms of PRR, V and Erem as given in equation (5.4)
rem1 2 3
max max
EVOF = max k *PRR +k * +k * [**]
V E (5.4)
Where k1, k2 and k3 are weights whose values are fixed based on the
technique used in (Ali et al, 2007)
k1+k2+k3 = 1 k1=0.6, k2 =0.2, k3 = 0.2
max(.) = maximum value
PRR = Packet Reception Rate between the nodes
V = Packet velocity between the nodes
Vmax = maximum Packet velocity offered by the nodes
Erem = Residual energy level of neighbour node
Emax = maximum energy assigned to nodes
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Eth = critical threshold energy (10% of the initial energy
value)
** = neighbour nodes with forward flag set to 1 alone and
Erem > Eth is considered for selection process.
(a) Modeling PRR metric
The effects of PRR over one hop distance is illustrated in
Figure 5.3. This model captures the PRR between two nodes. PRR is
defined as the probability of successful reception of packets between two
neighboring nodes. If PRR is high then it implies that link quality is good
and vice versa. In a constructive channel conditions, the nodes have full
connectivity, if their distance of separation is lesser than D1. This region is
defined as connected region. They are disconnected if they are separated by
a distance greater than D2. This region is defined as disconnected region.
The region that lies between D1 and D2 is defined as transition region. In
this region, the PRR fluctuates randomly based on the channel
characteristics.
Figure 5.3 Packet Reception Rate versus one hop distance
78
Then the PRR is modeled as below
1
0
1, d(S, N) D1
D2 d(S, N)PRR X ,D1 d(S, N) D2
D2 D1
0, d(S, N) D2
(5.5)
b
a
2 2
where . max{a,min{b,.}}
X €N(0, ) = Gaussian variable with variance
The values of D1 and D2 are configurable, which depends on the
operating transmission power level of the nodes and the environmental
condition which is modeled by the path loss exponent value ( ) and
standard deviation ( ) as shown in Table 5.2 and 5.3.
Table 5.2 Typical values of path loss exponent for various
environmental conditions
Environment (dB)
Free space 2Outdoor
Shadowed urban area 2.7 to 5
Line-of-sight 1.6 to 1.8Indoor
Obstructed 4 to 6
Table 5.3 Typical values of standard deviation for various
environmental conditions
Environment (dB)
Outdoor 4 to 12
Office- hard partition 7
Office- soft partition 9.6
Factory- line-of-sight 3 to 6
Factory- obstructed 6.8
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Let Dmax be the maximum distance between one hop nodes and L
be the number of discrete power levels represented by the set (P1, P2, P3
….PL) at which a node can be operated. Then the value of Dmax is
proportional to power level used provided the medium is constructive. Let
Popt be the optimal transmission power level that can be chosen from the
ordered set {Popt (P1, P2, P3 ….PL)}.
If Popt = P1, then delay involved in data transfer is increased as
the number of hops between the source and destination nodes are
increased. If Popt = PL , the quality of the transmitting signal may be good
due to high transmitting power, but a degradation in throughput can be
expected due to high channel contention. Hence selection of optimal
transmission power is required. The Popt selection is a function of delay and
energy consumption in network.
In any general wireless scenario, the PRR reflects the diverse
link qualities within the transmission range. The reception rate of the data
packets at the neighbor node j from node i in the environment of interest is
analyzed as below. The data packet is decoded correctly provided
SNR SNRth (acceptable SNR threshold). The SNR is calculated by
equation (5.6),
jt ij sij iSNR P – PL d – (Rx ) (5.6)
where dij Dmax = the maximum distance between nodes i and j to
communicate probabilistically
(Pt)i = Popt in dBm, the optimal transmitting power level of
node i
(Rxs)j = Receiver sensitivity of node j in dBm
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PL(dij) = Path loss experienced between node i and node j that
describes the medium characteristic which is
modeled by equation (5.7),
ij 0 ij 0PL d PL d +10log(d / d ) X (5.7)
where = path loss exponent that depends on the environmental
condition
X = zero-mean gaussian distributed random variable in (dB)
with standard deviation
From the above analysis when Pt = Popt, then
D2 = Dmax and D1 = maxD
3 (5.8)
where Dmax = maximum distance between one hop nodes
(b) Modeling Packet velocity metric
Packet velocity (V) is modeled as below:
d(S,D) d(N,D)V
Delay(S, N) (5.9)
where d(S,D)-d(N,D) = the progress made towards the destination by
forwarding packet
Delay(S,N) = total delay experienced by the RTR packet
from source node S to reach the next one hop
neighbouring node N which is modelled as
below:
c t p q b s
RoundTripTimeDelay (S,N) =T +T +T +T +T +T =
2(5.10)
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where Tc = time taken by S to obtain channel using CSMA/CA
Tt = packet transmission time
Tp = propagation delay
Tq = processing delay
Tb = queuing delay
Ts = sleep to active transition delay
When a source node S gets a packet to transmit, it must wait
until the neighbour node N wakes up. The one hop delay calculation is
independent of synchronization timing. The non-synchronization is
achieved by inserting the transmission time as one of the field in RTR
packet. When receiving node N replies to sensor node S, it inserts the RTR
transmission time in its reply. Once S receives the reply, it subtracts the
transmission time from the arrival time to calculate the round trip time. If
Packet velocity is high, then the probability of the packet to arrive before
the deadline is high and thus ensures real-time communication.
Let D2 = Dmax be the maximum distance that the node can
probabilistically communicate when Pt =Popt
Then the maximum Packet velocity Vmax offered by the nodes is
formulated as
maxmax
min
DV
Delay (5.11)
where Delaymin = minimum delay required to communicate to
neighbor node
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max
V
V= normalized metric for choosing neighbor with higher
velocity
The best next hop node is selected based on equation (5.4) and
(5.5).
The routing issue handler is a sub-module of the Routing
Management module which is invoked when the Neighborhood
Management module is unable to find any forwarding nodes due to void
issues (Chen and Varshney 2007).
5.1.4 Energy Management
In order to increase the network lifetime, the energy
consumption in each node needs to be kept at the minimal level. In the
proposed LAEER protocol, a separate module named Energy Management
is designed for this purpose. In the neighbor discovery process only the
forwarding nodes are required to send reply packets, therefore the non-
forwarding nodes are switched to sleep state. This results in a reduction in
their energy consumption. The forwarding nodes are switched from sleep
to active state as they are involved in data transfer.
(a) Energy modeling for network layer
The total energy spent by the nodes in the network to transmit
data packets from Source S towards the Destination D is given by
i-1 iopt
M
,P T
i=0
E(S,D,l) = E (N N ) (5.12)
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where,Popt
E(S,D,l) = energy spent to transfer ‘l’ data packets from
Source to Destination through intermediate nodes
using Popt
i-1 iT ,E (N N ) = total energy spent by the node Ni-1 to transfer the
data to optimal neighbor Ni
Ni = data transmitted to optimal neighbor selection
based on the forwarding metric equation (Here N0
= S and NM = D)
M = number of nodes involved in the transfer of data to
sink D
ET(Ni-1,Ni) = Ec + 1Ed (5.13)
where, Ec = energy spent in neighbor discovery process
l = number of data packets sent to Ni
Ed = energy spent for the transmission of data packet of fixed
size
The energy spent in the neighbor discovery process (Ec) is
classified into energy spent for non-forwarding and forwarding nodes.
Case 1: Energy spent for neighbor discovery by non-forwarding
node (Ni) where i = 0 (N0)
c t rRTR RTR
E =E +kE (5.14)
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where
tRTR
E energy spent for transmission of RTR packet at Popt
rRTR
E energy spent for reception of RTR packet
k = number of RTR Replies from forwarding neighbors
Case 2: Energy spent for neighbor discovery by forwarding
nodes (Ni) where i 0, M
c t rRTR RTR
E =2E +(k+1)E (5.15)
where additionaltRTR
E is due to transmission of RTR reply packet by
forwarding node Ni and the (k+1) is due to reception of RTR broadcast
packet by source S.
The Residual energy available to the nodes can be computed as
(N ) -rem i-1 max T(N ,N )i 1 i
E =E E (5.16)
where, Emax be the maximum available energy of each node in the network.
The model explained in this section ignores the energy
consumed during the idle and sleep state and considers only the active
state.
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Figure 5.4 Flow chart of the proposed LAEER protocol
5.2 RESULTS AND DISCUSSION OF LAEER PROTOCOL
The proposed LAEER protocol is simulated using the Network
Simulator (NS) version 2 with IEEE 802.15.4 MAC/PHY layers support
(Zheng and Lee 2004, xbeedigimesh24 2010). The performance of the
proposed LAEER protocol has been compared with MaxPRR,
Maxvelocity, MaxEr and AODV schemes in terms of PDR, Average end-
to-end delay and NEC in the network respectively.
86
The scalability analysis is investigated. The control overhead
analysis of the proposed LAEER protocol with AODV is also carried out.
5.2.1 Performance Metrics
(i) Control overhead: The total number of Request/Reply
packets sent in the network for a data packet to reach the
destination.
(ii) Average end-to-end delay: End-to-end delay is defined as
the time taken by the data packet to reach the destination
node. Average end-to-end delay is calculated by taking the
average of delays experienced by the entire packet received
at the destination.
(iii) Packet Delivery Ratio (PDR): PDR is calculated as the
ratio of the number of packets received at destination node
to the total number of data packets transmitted by the
source node within a distinct instance. This metric defines
reliability of data delivery.
(iv) Average energy consumption in the network: The
percentage of energy consumed in a node is the ratio of
energy consumed by the node to its initial energy. Then the
average energy consumption in the network is defined as
the average of the individual energy consumed by the
nodes.
(v) Hop count: It is defined as the total number of hops
required to forward the data packets from source node to
the destination node.
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5.2.2 Effect of PRR on One Hop Distance for various Transmitting
Power Levels
5.2.2.1 Shadowing model for outdoor environment
The sensor nodes have discrete power levels of operation and the
choice of transmission power level also has an impact on the packet
reception. Figure 5.5 shows the effect of PRR on one hop distance for
various transmitting power levels in an outdoor environment = 2.7, = 4
dB). Higher the transmitting power, the larger is the transmission range and
the better the link quality. But higher transmitting power has the side effect
of reducing the packet delivery ratio in a WSN due to increased channel
contention and interference effects. Hence an optimum choice of
transmitting power is required. It can be seen that PRR drastically reduces
for increase in one hop distance.
Figure 5.5 Effect of PRR on one hop distance for various
transmitting power levels in an outdoor environment
88
5.2.2.2 Shadowing model for indoor environment
The effect of PRR on one hop distance for various transmitting
power levels in an indoor environment ( = 4, = 7dB) is shown in Figure
5.6. It is observed that PRR decreases for increase in one hop distance for
indoor also.
Figure 5.6 Effect of PRR on one hop distance for various
transmitting power levels in an indoor environment
5.2.3 Effect of End-to-end Delay on One hop Distance for various
Transmitting Power Levels
5.2.3.1 Shadowing model for outdoor environment
The effect of end-to-end delay on one hop distance for various
transmitting power levels in an outdoor environment is shown in
Figure 5.7.
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Figure 5.7 Effect of end-to-end delay on one hop distance for various
transmitting power levels in an outdoor environment
The higher the transmission power, the less is the delay required
to reach the same distant node operated at low power level. However, due
to link quality and retransmission effect the delay involved may be
increased. Hence optimum choice of transmitting power is necessary as it
also has effect on the end-to-end delay.
5.2.3.2 Shadowing model for indoor environment
The effect of end-to-end delay on one hop distance for various
transmitting power levels in an indoor environment is shown in Figure 5.8.
It is inferred that, the transmission range is typically less due to the
obstructive medium and the average delay is typically high at the edge of
the communication range. Hence, depending on the environmental
conditions the appropriate model has to be considered for routing the data.
90
Figure 5.8 Effect of end-to-end delay on one hop distance for various
transmitting power levels in an indoor environment
From the simulation results, it is inferred that acceptable PRR
and end-to-end delay for both outdoor and indoor environment are
achieved when nodes are operated at 0dBm. Hence the nodes can be
operated at optimum transmitting power 0dBm.
In the next section, with this optimum transmitting power, the
effect of PRR and end-to-end delay on one hop distance for various
outdoor and indoor environment are analyzed.
5.2.4 PRR analysis for different and values based on Optimal
Transmitting Power Level Selection
The effect of PRR on one hop distance between two nodes for a
typical indoor and outdoor environment operated at optimal transmitting
power level Pt=0dBm is shown in Figure 5.9.
91
Figure 5.9 PRR analyses versus one hop distance for 0dBm
It is inferred that depending on the environmental conditions, the
transmission range varies for constant transmitting power level. Further,
the packet reception is typically high on the connected region regardless of
the nature of environment and decreases smoothly in transition region. But
in an ideal two ray ground model, perfect reception within transmission
range is observed which is not realistic. Choosing the forwarding node
based on PRR in the connected and transition region is the optimal solution
to increase the hop distance in order to reach the sink. Hence greedy
approach of neighbor selection will lead to a poor delivery ratio.
5.2.5 End-to-end Delay Analysis for different and values based
on Optimal Transmission Power Level Selection
The effect of variation in one hop distance between two nodes on
end-to-end delay for typical indoor and outdoor environment based on
optimal transmission power level Pt=0dBm is shown in Figure 5.10.
Though the propagation delay increases with increase in distance, the
retransmission on the unreliable links in the transition region will lead to an
increase in end-to-end delay.
92
Figure 5.10 End-to-end delay versus one hop distance for 0dBm
5.2.6 System Parameters for the Simulation of the Proposed
LAEER Protocol
The proposed LAEER protocol is simulated in NS2 with the
assumptions as presented in Table 5.4. The nodes are assumed to be static.
The propagation model of the medium is log normal shadowing. The
physical and MAC layer specifications are as per IEEE 802.15.4 standard.
Table 5.4 System parameters for simulation environment
Parameter Value
Propagation Model Shadowing Model
phyType Phy/WirelessPhy/802.15.4
macType Mac/802.15.4
Operation mode Non Beacon (Unslotted)
CSThresh_ 1.10765e-11 (-110dbm)
RXThresh_ 1.10765e-11 (-110dbm)
freq_ 2.4e+9
Initial Energy 3.6 Joules
TxPower/RxPower 0.02955/0.0255W
Transport layer UDP
Traffic type CBR
Packet Rate 5 packets/sec
Simulation time 100 sec
93
The sensor network deployment is considered to be grid
network. The transmission range of each node is restricted to 25 meters.
The nodes that are placed within 15-21meters range are assumed to have an
acceptable link quality. Figure 5.11 shows the average packet reception
rate for variation in one-hop distance for optimal transmission power value
0dBm modeled for outdoor environment. Based on these characteristics,
optimal transmission power level value, D1 and D2 values are selected.
The nodes placed within 15 meters are under a connected region. The
nodes placed beyond 30 meters range are under disconnected region. The
intermediate region between 15m and 30m is the transition region.
Figure 5.11 Average Packet Reception Rate for one hop distance
variation
5.2.7 Comparison of Proposed LAEER with Existing Schemes
The selection of optimal neighbor based on the maximum
weighted value of PRR, Packet velocity and Residual energy is compared
with MaxPRR, Maxvelocity, MaxEr, and AODV schemes in terms of
94
PDR, Average end-to-end delay, and NEC in network. The control
overhead analysis of the proposed LAEER with AODV is also performed.
Figure 5.12 Comparison of Packet Delivery Ratio for various schemes
Figure 5.12 shows PDR result of the proposed LAEER protocol
obtained with 25 nodes. The PDR of the proposed LAEER is
compared with four other schemes, namely, MaxPRR (Zhao and
Govindan 2003, Couto De et al 2003), Maxvelocity (Lu et al 2002, He et al
2003, Chipara et al 2006), MaxEr (Yu et al 2001, Razia Haider et al 2007)
and AODV (Elizabeth Royer and Charles Perkins 2000). It is found that
MaxPRR scheme exhibits good PDR as this scheme selects the
forwarding neighbor node from the connected region. The Maxvelocity
scheme exhibits lower packet delivery ratio, as this scheme selects the
forwarding node which offers maximum progress towards destination
node and it ignores the link quality issue. The MaxEr scheme
exhibits low delivery ratio as residual energy alone cannot stand as a
separate metric. Also, if node in connected region is selected, then
delivery ratio is improved. The AODV scheme does not consider the
95
residual energy of the node. It chooses the same route to forward
data to the sink node. This leads to the death of the nodes which reduces
the packet delivery ratio. The proposed LAEER exhibits a better PDR as
this scheme selects the forwarding node with maximum residual energy
and considerable velocity that lies in the connected region.
Figure 5.13 shows the Average end-to-end delay result of the
proposed LAEER protocol. The Average end-to-end delay of proposed
LAEER is compared with MaxPRR, Maxvelocity, MaxEr and AODV
schemes. In MaxPRR scheme, the packet suffers a greater end-to-end delay
as the number of hops is more. In Maxvelocity scheme, the packet takes
lesser end-to-end delay as the nodes that offer maximum progress towards
destination node are selected. In MaxEr scheme, the Average end-to-end
delay experienced by the packet lies between MaxPRR and Maxvelocity,
because the region in which the forwarding nodes lie is the deciding factor.
In AODV scheme the end-to-end delay is slightly less compared to
MaxPRR scheme as the number of hops is reduced. The Average end-to-
end of LAEER is less compared to MaxPRR, MaxEr and AODV.
Figure 5.13 Comparison of Average end-to-end delay for various
schemes
96
Figure 5.14 shows the NEC of the proposed LAEER protocol.
The NEC of LAEER is compared with four other schemes as detailed
before. It is found that MaxPRR scheme consume more energy in the
network as more nodes are involved in forwarding the data to destination
node. The Maxvelocity scheme consumes lesser energy than MaxPRR
scheme as number of nodes involved for packet transfer is less. The energy
consumption in MaxEr scheme is the same as MaxPRR. The Normalized
Energy Consumption in AODV scheme is higher as the overhead factor
involved is high. The proposed LAEER consumes less energy as the
selection of OF neighbor nodes are done based on the maximum weighted
value of Packet Reception Rate, Packet velocity and Residual energy.
Figure 5.14 Comparison of Normalized Energy Consumption for
various schemes
The sample Neighbor Table entries recorded by forwarding
nodes in proposed LAEER protocol is shown in Figure 5.15.
97
Figure 5.15 Snapshot of sample Neighbor Table entries
5.2.8 Scalability Analysis
Simulation studies are performed to validate the performance of
the proposed LAEER protocol for varying network sizes under regular and
random deployment. Figure 5.16, 5.17 and 5.18 show the results of the
variation in PDR, Average end-to-end delay and NEC under regular
deployment.
Figure 5.16 Packet Delivery Ratio of different schemes for different
network size under regular deployment
98
Figure 5.17 Average end-to-end delay of different schemes for
different network size under regular deployment
Figure 5.18 Normalized Energy Consumption of different scheme for
different network size under regular deployment
99
Figure 5.19, 5.20 and 5.21 present the results of variation in
PDR, end-to-end delay and Normalized Energy Consumption under
random deployment for varying network sizes.
Figure 5.19 Packet Delivery Ratio of different schemes for different
network size under random deployment
Figure 5.20 Average end-to-end delay of different schemes for
different network size under random deployment
100
Figure 5.21 Normalized Energy Consumption (NEC) of different
schemes for different network size under random
deployment
From the simulation studies, it is observed that the results in both
regular and random deployment cases are similar to those obtained in
Figure 5.12, 5.13 and 5.14.
5.2.9 Control Overhead
Figure 5.22 shows that LAEER achieves a smaller overhead
than AODV, since only a few nodes participate in the route discovery
process. AODV suffers huge overhead on high scalable wireless sensor
networks. In a small scale network (9 nodes), the overhead factor of
AODV shows a 20% increase compared to LAEER and this factor
increases and becomes dominant on high scale networks and suffers a 70%
increase compared to LAEER.
101
C
O
N
T
R
O
L
O
V
E
R
H
E
A
D 0
20
40
60
80
100
120
140
9 25 49 121
Number of Nodes
LAEER
AODV
Figure 5.22 Control Overhead Analysis
5.2.10 Complexity Analysis
Let formulating broadcast packets take p units of time. Let
receiving packets from (n-1) neighbors take q units of time. Let finding the
best neighbors based proposed methods take r units of time. Hence the
computation complexity involved in the proposed LAEER protocol is
O(2(n-1)(p + q + r)).
5.2.11 Real-Time Implementation
The deployment scenario presented in Figure 3.15, illustrates the
creation of WSNs test bed with sensor nodes. Figure 5.23 shows the
working environment of the test bed.
Figure 5.23 Working environment
102
The location information of the nodes determined by the proposed
ERSS based localization algorithm and the role of each node in the
deployment scenario is presented in Table 5.5.
Table 5.5 Location and role of sensor nodes
Sl.No. Node ID64 bit IEEE 802.15.4
ADDRESS
Location
(X,Y)Role of sensor node
1. BS 13A200402DD873 (35,23) COORDINATOR
2. NODE1 13A200402DD858 (40,23) ROUTER/END DEVICE
3. NODE2 13A200402DD867 (26,22) ROUTER/END DEVICE
4. NODE3 13A200402DD855 (4,26) ROUTER/END DEVICE
5. NODE4 13A200402DD853 (49,38) ROUTER/END DEVICE
6. NODE5 13A200402DD851 (6,36) ROUTER/END DEVICE
7. NODE6 13A200402DD850 (13,34) ROUTER/END DEVICE
8. NODE7 13A200402DD84D (53,34) ROUTER/END DEVICE
9. NODE8 13A200402DD89C (87,29) ROUTER/END DEVICE
10. NODE9 13A200402DD856 (40,37) ROUTER/END DEVICE
A snapshot illustrating the real-time implementation of the Proposed
LAEER protocol is shown in Figure 5.24 in which node 6 is the source that
transmit data to the sink node (BS).
Figure 5.24 WSN test bed to implement LAEER protocol
103
Table 5.6 and Table 5.7 present the entries of the Neighbor Table
of Node 6 and Node 9 observed during the implementation.
Table 5.6 Neighbor Table of Node 6
Source
Address
Destination
Address
Next hop
identifier
Next hop
64bit
address
Energy
value of
Next hop
id
Locationo
f Next
hop (X,Y)
Forward
Flag
13A20040
2DD850
13A200402D
D873(BS)
NODE7 13A200402
DD84D
FF (53,34) 0
NODE5 13A200402
DD851
FF (6,36) 0
NODE4 13A200402
DD853
FF (49,38) 1
NODE8 13A200402
DD89C
FF (87,29) 1
NODE9 13A200402
DD856
FF (40,37) 1
Table 5.7 Neighbor Table of Node 9
Source
Address
Destination
Address
Next hop
identifier
Next hop
64bit
address
Energy
value of
Next
hop id
Location
of Next
hop
(X,Y)
Forward
Flag
13A20040
2DD850
13A200402D
D873
BS 13A20040
2DD873
-- (35,23) 1
NODE1 13A20040
2DD858
FF (40,23) 1
NODE3 13A20040
2DD855
FF (4,26) 0
NODE4 13A20040
2DD853
FF (49,38) 0
The Base Station (sink) node repeatedly broadcasts the character
‘B’ along with its location (X, Y) to configure the network. The snapshots
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shown in Figure 5.25 present the nodes displaying the location information
of the sink and their distance to the sink.
Node 2 Node 4
Node 8 Node 9
Figure 5.25 Snapshots illustrating network configuration
The screenshot in Figure 5.26 shows that Node 6 has data to be
sent and hence broadcasts RTR packet and receives replies from
forwarding nodes.
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Count of Replies
from Forwarding
Nodes after RTR
broadcast
Nodes’ Location
and Residual
Energy Levels
Figure 5.26 Request To Route (RTR) generation from Source Node 6
The RTR replies from forwarding nodes are shown in
Figure 5.27 .
Figure 5.27 Request To Route Reply (RTR) from Forwarding nodes 4, 8, 9
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After the reception of RTR replies, the source node 6 chooses
the optimum node and sends the data packet. This process is repeated till
the data reaches the Base Station (sink).
The data packet received in Base Station Node is shown in
Figure 5.28.
Figure 5.28 X-CTU Snapshot of API frames received at Sink node
From the real-time experiment, the performance of the proposed
LAEER scheme is compared with the existing MaxPRR, Maxvelocity,
MaxEr and AODV schemes in terms of energy consumption. Using
equation 5.12, it is found that the average energy consumed by the
proposed LAEER scheme to transmit data from source node 6 to sink node
(BS) is 26.38% lesser than the existing MaxPRR, Maxvelocity, MaxEr and
AODV schemes.
The Table 5.8 shows the control and data zigbee packet formats
used in the real-time implementation of the proposed LAEER scheme. The
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major fields in the packet that differentiate control packet from data
packets are API ID, 64 bits destination address, 16 bits network address,
RF data and the last field checksum.
Table 5.8 Format of Control and data zigbee packets
Types of
packets
(Bytes)
LSB
(3)
API ID
(4)
Frame
ID (5)
64-bit Destination
Address (6-13)
16-bit
Destination
Network
Address (14-15)
Broadcast
Radius
(16)
RF Data
(18 –n)
CS
(last)
Broadcast
packet15 10 01
00 00 00 00 00 00
FF FFFF FE 00
42 53 52 45
41 44 59E9
Receive
packet13 90
00 13 A2 00 40 2D
D8 7300 00 02
42 53 52 45
41 44 59F6
Transmit
status07 8B 01 - FF FE 00 00 76
Neighbour
discover
packet
14 10 0100 00 00 00 00 00
FF FFFF FE 01
45 4E 44 31
08 FEE4
Data packet 14 10 0200 13 A2 00 40 2D
D8 55FF FE 01
44 4E 44 31
34 3530
The real-time implementation of LAEER has been implemented
for indoor environment and the performance has been validated. Thus the
proposed LAEER performance is better than MaxPRR, Maxvelocity,
MaxEr and AODV schemes.
