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International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 1 (2018) pp. 175-188
© Research India Publications. http://www.ripublication.com
175
The Impact of Dynamic Scaling on Energy Consumption at Node Level in
Wireless Sensor Networks
Rajan Sharma1 1 Research Scholar, Department of Electronics and Communication Engineering
I.K. Gujral Punjab Technical University, Jalandhar, Punjab, India.
Orcid: 0000-0001-9352-2833
Balwinder Singh Sohi2 2Department of Electronics and Communication Engineering
CGC Group of Colleges, Mohali, Punjab, India
Abstract
Energy efficiency is one of the critical issues in Wireless
Sensor Networks (WSNs) due to limited capacity of batteries
of its sensor nodes. This paper investigates the impact of
dynamic scaling of parameters such as modulation scheme,
voltage or frequency which reduces energy consumption of
sensor node. The performance is evaluated mathematically for
scaling of voltage and frequency dynamically. This approach is
used to dynamically adjust frequency and voltage of processing
unit according to actual system load to save computational
power without degrading its performance. We focused on the
fact that energy consumed by wireless sensor node is the
product of power consumed and the time for any operating
mode, the reduction in the value of either parameter such as
voltage, frequency and varying modulation scheme may result
in saving of huge energy. The impact of various modulation
schemes at different frequency bands and operating modes on
energy consumption of sensor node is evaluated using
QUALNET 6.01 Simulator.
Keywords: Wireless Sensor Networks, Sensor Node, Dynamic
Voltage Scaling (DVS), Dynamic Frequency Scaling (DFS),
Dynamic Modulation Scaling (DMS), Energy Consumption,
QUALNET 6.01.
INTRODUCTION
There are many parameters such as modulation scheme, voltage
or frequency which reduces power consumption of sensor node
by reducing the communication or computation time of the
radio-transceiver and processor respectively. We can save more
energy by dynamically adopting the modulation level
according to traffic load, known as modulation scaling (DMS)
[1, 2]. The same is applicable for voltage or frequency which is
known as voltage scaling and frequency scaling respectively [3,
4]. The major portion of the total energy consumption is spent
in communication as nodes which have to communicate with
each other and with the outside world are enabled by radio. It
has a radio of limited area communication which works on the
unlicensed radio frequency bands as defined by IEEE 802.15.4
standards i.e. 868 MHz (for Europe & Japan), 915 MHz (for
USA) and 2400 MHz (used worldwide) also known as ISM
radio band. The number of channels in 868 MHz band, 915
MHz band and 2400 MHz band are 1, 10 and 16 respectively.
Similarly, the data rate for these three bands are 20 kbps,
40kbps and 250 kbps respectively [5, 6, 7]. While
communicating in long distance, the sensors should avoid
direct communication with the sink node; instead it should
communicate using multi hop communication. Direct
communication means requirement of high transmission power
in order to achieve reliable transmission which leads to more
energy usage. Multiple paths should be chosen at different
times as the single optimized path will lose its energy if the
same path is chosen repeatedly for all the transmissions. The
paths should be chosen in a round robin manner. In this way the
energy is saved by using multi hop communication.
The features of Power consumption in the radio are affected by
various factors which contain operational duty cycle, data rate,
transmit power and various types of modulation schemes.
Transmit, Receive, idle and Sleep are the modes of operation in
any transceiver similar to microcontrollers. Every time it has
been observed that the maximum energy consumed by the
transceiver is in the idle mode so it is advised not to put the
transceiver in the idle mode, instead of it the transceiver should
be kept in sleep mode. Another influencing factor is that, the
transient activity state, which is known as the ON and OFF state
in the radio system consumes a substantial quantity of power as
the radio's operating mode changes. This causes dissipation of
energy and is considered as wastage of energy.
The rest of this paper is organized as follows. Section two
introduces brief summary related to energy consumption in a
sensor node. In section three, we briefly discuss the related
work focused on various scaling techniques and energy
consumption. Section four is focused on Basics of Dynamic
Voltage - Frequency Scaling (DVFS) Technique. In section
five, the simulation results and analysis is discussed based on
scaling of hardware parameters and modulation. Similarly,
energy consumption is compared based on operational mode,
frequency band, operational time and modulation scheme.
Finally, we present our conclusion and prospects in section six.
ENERGY CONSUMPTION IN A SENSOR NODE
WSNs are likely to run for a long time without human
intervention and with limited power in the sensor nodes, energy
consumption is critical issue in these types of networks. The
WSN applications [8, 9] are very broad, for example, military,
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 1 (2018) pp. 175-188
© Research India Publications. http://www.ripublication.com
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health info, environmental monitoring and smart home. The
radio transceiver in a sensor node is the primary consumer of
energy compared to other node components such as the
microprocessor or the sensing device. The radio can work in
four different modes of operation as Table 1 illustrates. The
first three modes i.e transmit, receive and listen, require
different level of power consumption which depends upon
various parameters but turning off the power of the radio port
while it is idle listening could save a large amount of energy.
Table 1: Modes of operation in a radio transceiver
Mode Comment
Transmit A node is transmit mode when its radio is
transmitting packets
Receive A node is in receive or reception mode when its
radio is receiving packets
Listen A node in listen mode when its radio is sensing
the channel and waiting for packets
Sleep A node is in sleep mode when its radio is
switched off
RELATED WORK
Energy consumption for computation and communication in
sensor nodes has been important concern as it firmly decide the
lifetime of node and networks. Reduction in energy
consumption based on hardware parameters such as voltage,
frequency as well as modulation technique has been a domain
of research for long. Maryam Bandari et al. [10] presented the
combined method that reduces the energy consumption in
wireless systems under probabilistic workloads, but they have
not focused on the impact of parameters like voltage or
frequency for energy consumption using DVS approach.
Similarly, the impact on the energy consumption using DMS
approach. Saeeda Usman et al. [11] reported a comparative
study of DVFS techniques on the basis of power reduction,
energy saving and performance. They have not explained, how
the variation in parameters such as voltage and frequency can
save time and energy consumption. Ulf Kulau et al. [12]
focused on hybrid DVS and DPM technique for power
optimization in sensor networks. They named this hybrid
approach as mod DVS which is the improved version of
classical DVS for improving the energy efficiency of processor,
transceiver, sensor and memories. This increases the lifetime of
sensor as well as the network, but they have not focused on the
impact of various modulation schemes on the energy
optimization. Bahareh Gholamzadeh et al. [13] has discussed
various sources of energy waste in WSNs, characteristics of
node hardware such as processing unit, communication device
(transceiver), sensing device and power supply device. They
also focused on various design approaches to minimize power
consumption and for prolonging the lifetime of node and
network. Sharma et al. [14-16] focused on sources of energy
waste, energy efficiency and lifetime of WSNs.
Our work differs from the above mentioned contributions as we
focused on the impact on energy consumption with variation of
hardware parameters such as voltage and clock frequency, data
rate, communication time, frequency band and modulation
scheme on the sensing node in WSNs.
BASICS OF DYNAMIC VOLTAGE FREQUENCY
SCALING (DVFS) TECHNIQUE
With the advancement in chip designing technology, the
controllers speed increased up to GHz, so the power dissipation
has also increased accordingly. The power of sensor nodes can
be reduced by designing ultra-low power CMOS chips as the
first step in this direction with feature of Dynamic Voltage
scaling (DVS) [17] or Dynamic Frequency Scaling (DFS) or
combination of both which is Dynamic Voltage and Frequency
Scaling (DVFS) [18]. There are two approaches to implement
DVS or DFS or DVFS. In first approach, the processing unit
can be switched to its full operational capacity mode to
compute the task at the fastest speed and then return back to the
sleep mode as soon as possible. The speed of the computational
task can be increased either by increasing voltage or frequency
within the specified limits as defined by data sheet in the
situation of high load. In alternative approach, the
computational task speed can be decreased, whenever there is
less load or no computational task or activity [19, 20, 21, 22].
In other words, compute the assigned task only at the required
minimum speed to finish the same before deadline.
Table 2: Effect of Dynamic Voltage Frequency Scaling (DVFS) on energy consumption
Processor Clock
Frequency
Range
(In MHz)
Voltage
Range
(In V)
Different
Scenarios
Operating
Clock
Frequency
(F)
(In MHz)
Operating
Voltage
(In V)
Power
Consumption
Reduction by
Factor(PCC1/
PCC 2)
Speed
Reduction
by Factor
(FC1/FC2)
Required Energy
Reduction per
instruction = Speed
Reduced Factor/ Power
Consumption Reduction
Factor (in %)
ATmega1284P 0-4 1.8–5.5 Case-1 4 3.3 6.72 2 29.76
Case-2 2 1.8
TI MSP430 0 – 16 1.8 - 3.6 Case-1 7 3.3 4.14 1.52 36.71
Case-2 4.6 2
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 1 (2018) pp. 175-188
© Research India Publications. http://www.ripublication.com
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We can trade-off between operating voltage and operating
frequency as mentioned in above approaches, the power
consumption can be reduced to some extent in CMOS chips. It
is a way of controlling and saving the energy usage in a sensor
node. It is the most efficient approach, which keeps track of the
system activities, input arrival and contributes significantly to
lifetime improvement by managing system components
activities. The Dynamic Power Management (DPM) technique
is implemented at the operating system of the sensor
node. Therefore, power saving using dynamic power
management and proper scheduling of input events is essential
for extending the lifetime of embedded sensor nodes [23].
The power dissipation of controller based on CMOS
technology is the integration of dynamic power and static
power [24, 25].
There are mainly two types of power consumption i.e. dynamic
power PDynamic and static power PStatic.
Mathematically, PCMOS = PDynamic + PStatic (1)
The dynamic power is comparatively major portion of the
CMOS power dissipation. It can be expressed as [26, 27]:
PDynamic= CL. v2. fc (2)
Where: CL= Parasitic capacitance and its value depends upon the
manufacturing process quality.
𝑣= Operating supply voltage
fc = Operating frequency of controller
INVESTIGATION AND ANALYSIS
Power Consumption Reduction Factor and Speed Reduction
can be calculated as mentioned below:
Power Consumption Reduction Factor =
Power Consumption in Case 1(PCC1) (3)
Power Consumption in Case 2 (PCC2)
Speed Reduction Factor =
Operating Frequency of Controller in Case 1(FC1) (4)
Operating Frequency of Controller in Case 2 (FC2)
Required Energy Reduction per instruction =
Speed Reduced Factor
Power Consumption Reduction Factor (5)
Table 2 reports the effect of Dynamic Voltage Frequency
Scaling (DVFS) on energy consumption, it has been observed
for ATmega1284P that by decreasing the operating frequency
from 4 MHz to 2 MHz i.e. reduced to half and decreasing the
operating voltage from 3.3 V to 1.8 V i.e. again almost half, the
power consumption is reduced by the factor of 6.72 but the
speed is reduced by the factor of 2 only. The required energy
per instruction is reduced by 29.76 %. Similarly, it has been
observed for TI MSP430 that by decreasing the operating
frequency from 7 MHz to 4.6 MHz and decreasing the
operating voltage from 3.3 V to 2 V, the power consumption is
reduced by the factor of 4.14 but the speed is reduced by the
factor of 1.52 only. The required energy per instruction is
reduced by approximately 36.71%
A. Effect of Operational Frequency Band on Energy
Consumption in Sensor Node
There is relation between operational frequency band, data rate,
transmission time and processing time. As the node switches to
higher frequency band, data rate increases accordingly as per
design specifications, further increase in data rate decreases the
transmission time of frame as shown in table 3 and Fig. 1. If
transmission time of frame decreases, then it also decreases the
idle time of the processing unit. This will decrease the energy
consumption of that particular sensing node as well as
prolonging battery life span and accumulation of this energy
saving at each node will increase the lifetime of network.
We know that Energy Consumption of sensing node may be
expressed as:
Time to send or receive per bit (T) = 1/ Data rate
Where the unit of data rate and time are Kbps and mS
respectively.
Table 3: Relation between frequency band, data rate and
communication time.
Frequency Band
(in MHz)
Maximum Data
Rate (in kbps )
Time to send or
Receive per bit (T)
(in mS)
868- 868.6 20 kbps .05
902-928 40 kbps .025
2400-2483.5 250 kbps .004
The Table 3 and Fig. 1 shows that the time required to send or
receive per bit in 868 MHz frequency band is highest,
comparatively less in 915 MHz band but least in 2400 MHz
band.
Figure 1: Communication time w.r.t frequency
band and data rate.
0.05
0.025
0.004
Time to send or Receive per bit (T) (in mS)
868- 868.6 MHz ,20 kbps
902-928 MHz ,40 kbps
2400-2483.5 MHz ,250 kbps
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 1 (2018) pp. 175-188
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Figure 2: Network scenario
B. Effect of Operational Frequency Band and Modulation
Scheme on Energy Consumption in Sensor Node
Simulation Model
The proposed network architecture in Fig. 2 is cluster of nine
Sensor nodes in the star topology and each node is 50 m apart
from each other in the specific target area of 100m * 100m in
the Terrain Size of 1000m * 1000 m. In the proposed simulation
environment, various parameters are considered at network and
node levels are represented in Table 4.
The main goal of this simulation setup is to investigate the
minimum energy consumption modulation scheme at various
frequency bands and operational modes. The various
simulation parameters used in the research are: operating
modes, modulation scheme, frequency band, and operational
time duration as well as battery energy consumption. The
tabular results that compare energy consumption for various
modulation schemes at different frequency bands for nodes
operating in transmit, receive and idle mode are represented in
the Table 5.
Table 4: Simulation parameters of network scenario.
Parameter Value
Simulator Qual Net 6.1
Terrain Size 1000 * 1000 Sq M.
No. of Nodes 9
MAC Protocol IEEE 802.15.4
Packet Reception Model PHY 802.15.4
Radio Type IEEE 802.15.4
Energy Model Micaz
Routing Protocol AODV
Antenna Model Omni directional
Network Protocol IPV 4
Device Type Sensor (FFD, RFD)
Traffic Type Constant Bit Rate (CBR)
Items to Send 100
Item Size 70 Bytes
Simulation Time 300 Seconds
Link Wireless
Channel Frequency 868 MHz, 915 MHz and
2400 MHz
Modulation ASK, BPSK, O-QPSK
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 1 (2018) pp. 175-188
© Research India Publications. http://www.ripublication.com
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Table: 5: Comparison of energy consumed (in mWh) node wise for various modulation schemes
at different frequency bands and operating modes.
Modulation
Scheme
Mode Frequency
(In MHz)
Energy Consumed (in mWh) Node wise
1 (RFD) 2 (RFD) 3(RFD) 4(RFD) 5(RFD) 6(RFD) 7(RFD) 8(RFD) 9(FFD)
O- QPSK Transmit 2400 0.008222 0.008046 0.008663 0.008397 0.00859 0.008438 0.007907 0.00793 0.125453
Receive 0.102739 0.104157 0.105171 0.103779 0.110334 0.103991 0.104403 0.10212 0.041334
Idle 0.009096 0.011228 0.01225 0.010678 0.352167 0.010047 0.012038 0.011639 0.870323
O- QPSK Transmit 868 0.020863 0.021028 0.022459 0.023309 0.024786 0.022963 0.023902 0.022287 0.155127
Receive 0.130413 0.117561 0.120767 0.132149 0.136819 0.120177 0.133989 0.118995 0.123647
Idle 0.345648 0.02855 0.033511 0.335902 0.353176 0.024039 0.385093 0.032863 0.849648
O- QPSK Transmit 915 0.008466 0.008152 0.008663 0.008612 0.008628 0.008521 0.007724 0.007756 0.125385
Receive 0.104002 0.103347 0.105877 0.103608 0.110639 0.105953 0.103256 0.101116 0.041717
Idle 0.010507 0.01297 0.012512 0.011103 0.354201 0.011244 0.011218 0.010697 0.870261
BPSK Transmit 868 0.095039 0.082823 0.109749 0.061906 0.103851 0.087755 0.081445 0.096726 0.661429
Receive 0.440904 0.436874 0.453453 0.415055 0.533847 0.455082 0.473621 0.515974 0.524298
Idle 0.037071 0.037787 0.038982 0.03233 0.301621 0.032242 0.049518 0.288318 0.688585
BPSK Transmit 915 0.061635 0.058381 0.058238 0.05339 0.06133 0.05297 0.060063 0.052042 0.544465
Receive 0.455345 0.430075 0.428959 0.416046 0.429333 0.419108 0.421619 0.41272 0.267073
Idle 0.291903 0.028985 0.025379 0.026133 0.028446 0.025809 0.021303 0.019163 0.75724
ASK Transmit 868 0.008538 0.007494 0.007374 0.008907 0.010178 0.009619 0.007314 0.006436 0.038027
Receive 0.029715 0.024322 0.025106 0.028716 0.031287 0.028079 0.026716 0.024922 0.046674
Idle 0.375179 0.019578 0.019246 0.381561 0.365101 0.382841 0.309155 0.034538 0.883903
ASK Transmit 915 0.007962 0.007708 0.007617 0.008521 0.008406 0.008266 0.007654 0.008495 0.100189
Receive 0.091106 0.08263 0.081837 0.083991 0.090393 0.08408 0.081757 0.08725 0.041252
Idle 0.373767 0.010123 0.012515 0.009892 0.360741 0.008864 0.009947 0.404 0.874557
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 1 (2018) pp. 175-188
© Research India Publications. http://www.ripublication.com
180
Figure 3: Comparison of energy consumed (in mWh) node
wise for different modulation schemes at 868 MHz in transmit
mode
The graph in Fig. 3 represents the comparison of energy
consumed (in mWh) node wise for different modulation
schemes at 868 MHz in transmit mode. The red line clearly
shows that the consumption of energy is higher using BPSK
modulation scheme, blue line represents that energy
consumption is less using O-QPSK compared to BPSK.
Similarly, grey line represents that energy consumption is least
using ASK as compared to other modulation schemes such as
BPSK and O- QPSK. It also shows that the energy consumption
is approximately same using O-QPSK or ASK modulation
scheme in the case of RFD nodes except FFD node.
Figure 4: Comparison of energy consumed (in mWh) node
wise for different modulation schemes at 868 MHz in receive
mode.
The graph in Fig. 4 shows the comparison of energy consumed
(in mWh) node wise for different modulation schemes at 868
MHz in receive mode. The red line clearly shows that the
consumption of energy is higher using BPSK modulation
Scheme, blue line represents that energy consumption is less
using O-QPSK compared to BPSK. Similarly, grey line
represents that energy consumption is least using ASK as
compared to BPSK and O-QPSK
Figure 5: Comparison of energy consumed (in mWh) node
wise for different modulation schemes at 868 MHz in idle
mode.
The Fig. 5 represents the consumption of energy (in mWh)
node wise for different modulation schemes at 868 MHz in idle
mode. The graphs clearly demonstrate that the consumption of
energy is on higher side in majority of the nodes using ASK
modulation scheme as indicated by grey line. Similarly, red line
represents that energy consumption is least in majority of nodes
using BPSK as compared to ASK and O-QPSK.
Figure 6: Comparison of energy consumed (in mWh) node
wise for different modulation schemes at 915 MHz in transmit
mode.
The graph in Fig. 6 represents the comparison of energy
consumed (in mWh) node wise for different modulation
00.20.40.60.8
En
erg
y C
on
sum
ed
(in
mW
h)
Modulation Scheme and Node ID
Comparison for Energy Consumption in Transmit
Mode at 868 MHz
O- QPSK Transmit mode
BPSK Transmit mode
ASK Transmit mode
00.10.20.30.40.50.6
En
erg
y C
on
sum
ed
(in
mW
h)
Modulation Scheme and Node ID
Comparison for Energy Consumption in Receive
Mode at 868 MHz
O- QPSK Receive modeBPSK Receive modeASK Receive mode
00.20.40.60.8
1
En
erg
y C
on
sum
ed
(in
mW
h)
Modulation Scheme and Node ID
Comparison for Energy Consumption in Idle Mode at
868 MHz
O- QPSK Idle mode BPSK Idle mode
ASK Idle mode
00.10.20.30.40.50.6
En
erg
y C
on
sum
ed
(in
mW
h)
Modulation Scheme and Node ID
Comparison for Energy Consumption in Transmit
Mode at 915 MHz
O- QPSK Transmit mode BPSK Transmit mode
ASK Transmit mode
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 1 (2018) pp. 175-188
© Research India Publications. http://www.ripublication.com
181
schemes at 915 MHz in transmit mode. The red line clearly
shows that the consumption of energy is higher using BPSK
modulation Scheme, blue line represents that energy
consumption is less using O-QPSK compared to BPSK.
Similarly, grey line represents that energy consumption is least
using ASK but approximately same as using O- QPSK as
compared to BPSK.
Figure 7: Comparison of energy consumed (in mWh) node
wise for different modulation schemes at 915 MHz in receive
mode.
The graph in Fig. 7 shows the comparison of energy consumed
(in mWh) node wise for different modulation schemes at 915
MHz in receive mode. The red line which represents BPSK
modulation scheme, it clearly shows that the consumption of
energy is highest in comparison with other modulation
technique, blue line represents that energy consumption is less
using O-QPSK compared to BPSK. Similarly, grey line
represents that energy consumption is least using ASK as
compared to BPSK and O- QPSK.
Figure 8: Comparison of energy consumed (in mWh) node
wise for different modulation schemes at 915 MHz in idle
mode.
The Fig. 8 represents the consumption of energy (in mWh)
node wise for different modulation schemes at 915 MHz in idle
mode. The graphs clearly demonstrate that the consumption of
energy is higher using ASK modulation scheme as indicated by
grey line, blue line represents that energy consumption is less
using O-QPSK compared to ASK. Similarly, red line represents
that energy consumption is least in sensing nodes using BPSK
as compared to ASK and O-QPSK.
The Fig. 9 draws a comparative analysis of energy consumption
for various operating modes such as transmit, receive and idle
mode using O-QPSK modulation schemes at 2400 MHz
frequency band related to all RFD nodes ( node no. 1 to 8) and
specific node: 9 which is Full Functional Device (FFD). The
figure represents that energy consumption is on comparatively
higher side in receive mode for all RFD’s except FFD and
energy consumption is minimum for transmission for all the
RFD’s except FFD. The energy consumed in transmit mode
and idle mode is approximately same in majority of RFD’s
except node 5 and FFD which is comparatively high.
Figure 9: Comparison of energy consumed (in mWh) node
wise for O-QPSK modulation schemes at 2400 MHz in
transmit, receive and idle mode.
00.10.20.30.40.5
En
erg
y C
on
sum
ed
(in
mW
h)
Modulation Scheme and Node ID
Comparison for Energy Consumption in Receive
Mode at 915 MHz
O- QPSK Receive mode BPSK Receive mode
ASK Receive mode
0
0.2
0.4
0.6
0.8
1
En
erg
y C
on
sum
ed
(in
mW
h)
Modulation Scheme and Node ID
Comparison for Energy Consumption in Idle Mode at
915 MHz
O- QPSK Idle mode BPSK Idle mode
ASK Idle mode
0
0.2
0.4
0.6
0.8
1
En
erg
y C
on
sum
ed
(in
mW
h)
Communication Mode and Node ID
Comparison for Energy Consumption in Transmit,
Reecive and Idle Mode For O-QPSK Modulation Scheme
at 2400 MHz
Transmit Receive Idle
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 1 (2018) pp. 175-188
© Research India Publications. http://www.ripublication.com
182
Table 6: Total charge consumed by battery (in mAhr) for various modulation schemes at different
frequencies related to Node: 9 (FFD)
Modulation Scheme Frequency Band
(In MHz)
Frequency
(In MHz)
Node ID : 9 (FFD)
Total Charge Consumed by
Battery (in mAhr)
O- QPSK 2400 - 2483.5 2400 0.35
O- QPSK 868 - 868.6 868 0.38
O- QPSK 902 - 928 915 0.35
BPSK 868 - 868.6 868 0.62
BPSK 902 - 928 915 0.52
ASK 868 - 868.6 868 0.32
ASK 902 - 928 915 0.34
Figure 10: Comparison of total charge consumed by battery (in mAhr) for various modulation schemes at different frequencies
related to node: 9 (FFD)
The Table 6 and Fig. 10 draws a comparative analysis of total
charge consumed by battery (in mAhr) for the same network
using various modulation schemes at different frequency band
related to specific node: 9 which works as Full Functional
Device (FFD). The above figure represents that the battery
charge consumption is maximum for BPSK modulation
scheme at 868 MHz and battery charge consumption is
minimum for ASK modulation scheme at 868 MHz frequency
band. The charge consumption by ASK and O-QPSK
modulation scheme is approximately same as it ranges from
0.32 to 0.38 irrespective of frequency band. The merit of using
O-QPSK modulation at 2400 MHz frequency band is high data
rate i.e. 250 kbps as compared to ASK modulation scheme at
868 MHz. The graph clearly shows that the charge
consumption in case of BPSK modulation is approximately 1.5
to 2 times higher as compared to ASK and O-QPSK which is
not recommended as energy is most precious in sensor
networks.
C. Effect of Operational Frequency Band and Modulation
Scheme on Operational Mode Time in Sensor Node
The tabular results that compares percentage of operational
time for various modulation schemes at different frequency
bands for nodes operating in transmit, receive, idle and sleep
mode are represented in the Table 7.
0.350.38
0.35
0.62
0.52
0.32 0.34
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
2400MHz
868MHz
915MHz
868MHz
915MHz
868MHz
915MHz
O- QPSK O- QPSK O- QPSK BPSK BPSK ASK ASK
Tota
l Ch
arge
Co
nsu
me
d b
y B
atte
ry (
in m
Ah
r)
Modulation Scheme and Frequency
Battery Consumption of Node: 9 (FFD)
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183
Table 7: Comparison of time (in Percentage) for different modes of operation (node wise) with various modulation schemes and
frequency bands.
Modulation
Scheme
Mode Frequency
(In MHz)
Operating Time (in %) Node wise
1 (RFD) 2 (RFD) 3(RFD) 4(RFD) 5(RFD) 6(RFD) 7(RFD) 8(RFD) 9(FFD)
O- QPSK Transmit 2400 0.152693 0.149429 0.160885 0.155947 0.159531 0.156704 0.146848 0.147285 2.32992
Receive 2.18206 2.21218 2.23373 2.20415 2.34338 2.20865 2.21742 2.16893 0.877889
Idle 1.01162 1.24866 1.36234 1.18749 39.1659 1.11737 1.33876 1.29441 96.7922
Sleep
Mode
96.6536 96.3897 96.243 96.4524 58.3311 96.5173 96.297 96.3894 -
O- QPSK Transmit 868 0.387467 0.390533 0.41712 0.432907 0.46032 0.42648 0.44392 0.41392 2.88104
Receive 2.76984 2.49688 2.56496 2.80669 2.90589 2.55243 2.84579 2.52733 2.62614
Idle 38.441 3.17514 3.72685 37.357 39.2782 2.67351 42.8278 3.65485 94.4928
Sleep
Mode
58.4017 93.9374 93.2911 59.4034 57.3556 94.3476 53.8825 93.4039 -
O- QPSK Transmit 915 0.157237 0.151392 0.160885 0.159936 0.160235 0.158261 0.143456 0.144043 2.32866
Receive 2.2089 2.19499 2.24872 2.20053 2.34986 2.25033 2.19306 2.14761 0.886019
Idle 1.16849 1.44245 1.39154 1.23482 39.3922 1.25044 1.2476 1.18971 96.7853
Sleep
Mode
96.4654 96.2112 96.1988 96.4047 58.0977 96.341 96.4159 96.5186 -
BPSK Transmit 868 1.76507 1.5382 2.03827 1.14973 1.92873 1.6298 1.5126 1.7964 12.2841
Receive 9.36433 9.27873 9.63087 8.81533 11.3383 9.66547 10.0592 10.9587 11.1355
Idle 4.12284 4.20249 4.33533 3.59551 33.5445 3.58579 5.50714 32.065 76.5803
Sleep
Mode
84.7478 84.9806 83.9955 86.4394 53.1885 85.1189 82.9211 55.1799 -
BPSK Transmit 915 1.1447 1.08427 1.0816 0.991567 1.13903 0.983767 1.1155 0.966533 10.1119
Receive 9.67103 9.13434 9.11063 8.83637 9.11857 8.9014 8.95473 8.76573 5.67234
Idle 32.4637 3.22355 2.82249 2.90635 3.16359 2.87036 2.36914 2.13119 84.2158
Sleep
Mode
56.7206 86.5578 86.9853 87.2657 86.5788 87.2445 87.5606 88.1365 -
ASK Transmit 868 0.158565 0.139179 0.13696 0.165413 0.189029 0.17864 0.135845 0.119513 0.706251
Receive 0.631105 0.516582 0.533224 0.609894 0.664503 0.596374 0.56742 0.529317 0.991304
Idle 41.7252 2.17733 2.14039 42.435 40.6044 42.5773 34.3824 3.84115 98.3024
Sleep
Mode
57.4851 97.1669 97.1894 56.7897 58.5421 56.6476 64.9144 95.51 -
ASK Transmit 915 0.147877 0.143147 0.141456 0.158251 0.156123 0.153515 0.142155 0.157765 1.86073
Receive 1.935 1.75498 1.73812 1.78387 1.91984 1.78577 1.73644 1.85309 0.876158
Idle 41.5682 1.12581 1.39186 1.10018 40.1195 0.98585 1.10626 44.9305 97.2631
Sleep
Mode
56.3489 96.9761 96.7286 96.9577 57.8045 97.0749 97.0151 53.0587 -
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 1 (2018) pp. 175-188
© Research India Publications. http://www.ripublication.com
184
Figure 11: Comparison of transmit time (in %) node wise for
different modulation schemes at 868 MHz
The graph in Fig. 11 represents the comparison of transmit time
(in %) node wise for different modulation schemes at 868 MHz
The red line clearly shows that the transmitting time is higher
using BPSK modulation scheme, blue line represents that
transmitting time is less using O-QPSK compared to BPSK.
Similarly, grey line represents that transmitting time is least
using ASK as compared to other modulation schemes such as
BPSK and O-QPSK. It also shows that the time duration for
transmission is approximately same using O-QPSK or ASK
modulation scheme in the case of RFD nodes except FFD node.
Figure 12: Comparison of receiving time (in %) node wise
for different modulation schemes at 868 MHz
The graph in Fig.12 shows the comparison of receiving time
(in %) node wise for different modulation schemes at 868 MHz
The red line clearly shows that the time for receiving is highest
using BPSK modulation scheme, blue line represents that
receiving time is less using O-QPSK compared to BPSK.
Similarly, grey line represents that receiving time is least using
ASK as compared to BPSK and O-QPSK.
0
2
4
6
8
10
12
14
Percen
tag
e o
f ti
me
Modulation scheme & Node ID
Comparison of time duration in Transmit Mode at 868
MHz
O- QPSK Transmit mode 868 MHz
BPSK Transmit mode 868 MHz
ASK Transmit mode 868 MHz
0
2
4
6
8
10
12
Percen
tag
e o
f T
ime
Modulation Scheme & Node ID
Comparison of time duration in Receive Mode at 868
MHz
O- QPSK Receive mode 868 MHz
BPSK Receive mode 868 MHz
ASK Receive mode 868 MHz
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 1 (2018) pp. 175-188
© Research India Publications. http://www.ripublication.com
185
Figure 13: Comparison of idle time (in %) node wise for
different modulation schemes at 868 MHz
The Fig. 13 represents the comparison of idle time (in %) node
wise for different modulation schemes at 868 MHz. The graphs
clearly demonstrate that the idle time is on higher side in
majority of the nodes using ASK modulation scheme as
indicated by grey line. Similarly, red line represents that idle
time is least using BPSK as compared to ASK and O- QPSK.
Figure 14: Comparison of sleep time (in %) node wise for
different modulation schemes at 868 MHz
The Fig. 14 represents the comparison of sleep time (in %) node
wise for different modulation schemes at 868 MHz. The graphs
clearly demonstrate that the sleep time is on higher side as 5
RFD’s nodes are in the range of (93-94) % using O-QPSK
modulation scheme as indicated by blue line. The sleep time is
in the range of (83- 86) % in 6 RFD nodes using BPSK
modulation scheme. Similarly, red line represents that sleep
time in least number of nodes as only 3 nodes have high sleep
time i.e. in the range of (95- 97) % using ASK as compared to
other modulation schemes i.e. BPSK and O- QPSK. It has
been observed that sleep time for FFD node is negligible in star
topology for all the above mentioned modulation schemes.
Figure 15: Comparison of transmit time (in %) node wise for
different modulation schemes at 915 MHz
The graph in Fig. 15 represents the comparison of transmit time
(in %) node wise for different modulation schemes at 915MHz.
The grey line clearly shows that the transmission time is on
higher side using ASK modulation scheme, red line represents
that transmission time is less using BPSK compared to ASK.
Similarly, blue line represents that transmission time is least
using O-QPSK as compared to ASK and BPSK. It also shows
that the time duration for transmitting is approximately close to
each other using all the above mentioned modulation scheme
in the case of RFD nodes except FFD node.
0
20
40
60
80
100
120
Percen
tag
e o
f T
ime
Modulation Scheme & Node ID
Comparison of time duration in Idle Mode at 868
MHz
O- QPSK Idle mode 868 MHz
BPSK Idle mode 868 MHz
ASK Idle mode 868 MHz
0
20
40
60
80
100
120
Percen
tag
e o
f T
ime
Modulation Scheme & Node ID
Comparison of time duration in Sleep Mode at 868 MHz
O- QPSK Sleep Mode 868 MHz
BPSK Sleep Mode 868 MHz
ASK Sleep Mode 868 MHz
0
1
2
3
4
5
6
7
Percen
tag
e o
f T
ime
Modulation Scheme & Node ID
Comparison of time duration in Transmit Mode at 915
MHz
ASK Transmit mode 915 MHz
BPSK Transmit mode 915 MHz
O- QPSK Transmit mode 915 MHz
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 1 (2018) pp. 175-188
© Research India Publications. http://www.ripublication.com
186
Figure 16: Comparison of receiving time (in %) node wise
for different modulation schemes at 915 MHz
The graph in Fig. 16 shows the comparison of receiving time
(in %) node wise for different modulation schemes at 915 MHz.
The red line clearly shows that the time for receiving is highest
using BPSK modulation scheme, blue line represents that
receiving time is less using O-QPSK compared to BPSK.
Similarly, grey line represents that receiving time is least using
ASK as compared to others i.e. BPSK and O-QPSK. It is
observed that the time duration for receiving using ASK and
O-QPSK modulation scheme is approximately close to each
other in the case of RFD nodes and FFD node.
Figure 17: Comparison of idle time (in %) node wise for
different modulation schemes at 915 MHz
The Fig. 17 represents the Comparison of idle time (in %) node
wise for different modulation schemes at 915 MHz. The graphs
clearly demonstrate that the idle time is on higher side in
majority of the nodes using ASK modulation scheme as
indicated by grey line. Similarly, red line represents that idle
time is least in majority of nodes using BPSK as compared to
ASK and O- QPSK.
Figure 18: Comparison of sleep time (in %) node wise for
different modulation schemes at 915 MHz.
The Fig. 18 represents the comparison of sleep time (in %) node
wise for different modulation schemes at 915 MHz. The graphs
clearly demonstrate that the sleep time is on higher side (above
96%) in majority of the RFD nodes (7 sensor nodes) using
O-QPSK modulation scheme as indicated by blue line. The
sleep time is in the range of (96- 97) % in 6 sensor nodes
(RFD’s) using ASK modulation scheme, which is represented
by grey line. Similarly, red line represents that sleep time is in
the range of (86-87) % in majority of RFD i.e. 7 sensor nodes
using BPSK modulation scheme which is less in comparison to
O-QPSK and ASK modulation scheme. It has been observed
that sleep time for FFD node is negligible in star topology for
all the above mentioned modulation schemes.
0
2
4
6
8
10
12
Percen
tag
e o
f T
ime
Modulation Scheme & Node ID
Comparison of time duration in Receive Mode at 915
MHz
O- QPSK Receive mode 915 MHz
BPSK Receive mode 915 MHz
ASK Receive mode 915 MHz
0
20
40
60
80
100
120
Percen
tag
e o
f T
ime
Modulation Scheme & Node ID
Comparison of time duration in Idle Mode at 915 MHz
O- QPSK Idle mode 915 MHz
BPSK Idle mode 915 MHz
ASK Idle mode 915 MHz
0
20
40
60
80
100
120
Percen
tag
e o
f T
ime
Modulation Scheme & Node ID
Comparison of time duration in Sleep Mode at 915 MHz
O- QPSK Sleep Mode 915 MHz
BPSK Sleep Mode 915 MHz
ASK Sleep Mode 915 MHz
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 1 (2018) pp. 175-188
© Research India Publications. http://www.ripublication.com
187
Figure 19: Comparison of time (in %) for O-QPSK in
transmit, receive, idle and sleep mode at 2400 MHz
The Fig. 19 draws a comparative analysis of operational time
for various operating modes such as transmit, receive, idle and
sleep mode using O- QPSK modulation schemes at 2400 MHz
frequency band related to all RFD nodes (Node no. 1 to 8) and
specific node: 9 which works as Full Functional Device (FFD).
The above figure represents that operating time is on
comparatively higher side i.e. 96% in sleep mode for majority
of RFD’s except node no.5 which is 58% and FFD which is
zero. The energy consumption in receive mode is approximately
2% for all RFD’s except FFD. The energy consumption is
around 1% in all RFD’s except node no 5 which is 39% and for
FFD which is 96.79% in the idle mode. It is observed that
transmit time is on very lower side in comparison to sleep
mode, receive mode and idle mode.
CONCLUSION
We simulate the proposed work with 8 RFD’s and 1 FFD to
investigate the impact of various scaling techniques such as
voltage, frequency and modulation on the energy consumption
of sensor node. It is observed that for specific node i.e. node no.
9 which is Full Functional Device (FFD), the maximum battery
consumption is occurred using BPSK modulation scheme at
868 MHz and comparatively less by using BPSK modulation
scheme at 915MHz. The battery consumption using O-QPSK
modulation scheme is less as compared to BPSK modulation
scheme. In the specific case of O-QPSK, the battery
consumption is on higher side at 868 MHz compared to 915
MHz and 2400 MHz, but the energy consumption using O-
QPSK modulation is almost same for 915 MHz and 2400 MHz.
The battery consumption is least using ASK modulation
scheme as compared to other modulation scheme such as BPSK
and O-QPSK. In the specific case of using ASK, battery
consumption at 915 MHz is slightly higher compared to 868
MHz. It has been concluded that BPSK modulation is not
recommended as it decreases the battery life span of sensor
node which further reduces the lifetime of Wireless sensor
network. If we compare ASK and O-QPSK, the battery
consumption is least for ASK at 868 MHz which is
approximately same as for O-QPSK at 2400 MHz. The
advantage of using O-QPSK at 2400 MHz is higher data rate
(250 Kbps) as compared to ASK at 868 MHz whose data rate
is 20 Kbps at the cost of almost same battery consumption. The
scaling is the trade-off decision between energy efficiency node
performance according to user priority and requirement. This
work strongly recommends the necessity of using combined
DVFS – DMS approach which can significantly increase the
life span of sensor node battery. The proposed investigation
opens a lot of research gates for the future researchers to
optimize the battery consumption and to prolong sensor node
lifetime.
ABBREVIATIONS
WSNs Wireless Sensor Networks
DVS Dynamic voltage Scaling
DFS Dynamic Frequency Scaling
DVFS Dynamic Voltage and Frequency Scaling
DMS Dynamic Modulation Scaling
DPM Dynamic Power Management
USA United States of America
ISM Industrial, Scientific and Medical
CMOS Complementary Metal Oxide Semiconductor
AODV Ad hoc On-Demand Distance Vector
FFD Full Functional Device
RFD Reduced Functional Device
CBR Constant Bit Rate
ASK Amplitude-Shift Keying
BPSK Binary Phase Shift Keying
O- QPSK Offset Quadrature Phase Shift Keying
REFERENCES
[1] C. Schurgers, V. Raghunathan, and M. B. Srivastava,
"Power management for energy-aware communication
systems," ACM Transactions on Embedded Computing
Systems, vol. 2, no. 3, pp. 431-447, 2003.
[2] V. Raghunathan, C. Schurgers, S. Park, and M. B.
Srivastava, "Energyaware wireless microsensor
networks," Signal Processing Magazine, IEEE, vol. 19,
no. 2, pp. 40-50, 2002.
[3] Y. Seo, J. Kim, and E. Seo, “Effective analysis of DVFS
and DPM in mobile devices,” Journal of Computer Science and Technology, Vol. 27, No. 4, July 2012, pp.
781-790.
0
20
40
60
80
100
120
Percen
tag
e o
f T
ime
Communication mode & Node ID
Comparison of time duration in O-QPSK Transmit
Mode, Receive Mode,Idle Mode, Sleep Mode at 2400
MHz
O- QPSK Transmit mode 2400 MHz
O- QPSK Receive mode 2400 MHz
O- QPSK Idle mode 2400 MHz
O- QPSK Sleep Mode 2400 MHz
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 1 (2018) pp. 175-188
© Research India Publications. http://www.ripublication.com
188
[4] J. Shuja, S. A. Madani, K. Bilal, K. Hayat, S. U. Khan,
and S. Sarwar, “Energy-efficient data centers,”
Computing, Vol. 94, No. 12, 2012, pp. 973-994.
[5] QualNet 6.1Sensor Networks Model
Library,September2012, pp.14,Scalable Network
Technologies, Inc., http://www.scalable-networks.com
[6] Liu Yanfei, Wang Cheng, Qiao Xiaojun, Zhang Yunhe,
Yu chengbo,Liu Yanfei, “An Improved Design of
ZigBee Wireless Sensor Network”, IEEE 2009.
[7] Chia-Ping Huang, “Zigbee Wireless Network
Application Research Case Study Within Taiwan
University Campus”, Proceedings of the Eighth
International Conference on Machine Learning and
Cybernetics, Baoding, 12-15 July 2009.
[8] Y. Zatout, R. Kacimi, J-F. Llibre and E. Campo:
Mobility-aware Protocol for Wireless Sensor Networks
in Health-care Monitoring: Fifth IEEE: International
Workshop on Personalized Networks, USA (2011).
[9] S. Zhao and D. Raychaudhuri: Multi-tier Ad hoc Mesh
Networks with Radio Forwarding Nodes: IEEE Global
Telecommunications Conference, IEEE GLOBECOM
2007, Washington, USA (2007).
[10] M. Bandari, R. Simon and H. Aydin, "Energy
management of embedded wireless systems through
voltage and modulation scaling under probabilistic
workloads," 2014 International Green Computing Conference (IGCC), DALLAS, TX, USA, 2014, pp. 1-
10. doi:10.1109/IGCC.2014.7039168
[11] Usman, Saeeda & U. Khan, Samee & Khan, Sikandar.
(2013). A comparative study of voltage/frequency
scaling in NoC. IEEE International Conference on
Electro Information Technology. 1-5.
10.1109/EIT.2013.6632716.
[12] U. Kulau, F. Busching and L. Wolf, "A Node's Life:
Increasing WSN Lifetime by Dynamic Voltage
Scaling," 2013 IEEE 9th International Conference on Distributed Computing in Sensor Systems (DCoSS 2013) (DCOSS), Cambridge, MA, 2013, pp. 241-248.
doi:10.1109/DCOSS.2013.39
[13] Bahareh Gholamzadeh, and Hooman Nabovati,
“Concepts for Designing Low Power Wireless Sensor
Network World Academy of Science, Engineering and
Technology,” International Journal of Electronics and
Communication Engineering, Vol: 2, No: 9, 2008.
[14] R. Sharma, B.S Sohi, N. Mittal, “Hierarchical Energy
Efficient MAC protocol for Wireless Sensor Networks”.
International Journal of Applied Engineering Research,
Volume 12, Number 24, 2017, pp. 14727-14738.
[15] R. Sharma, B.S Sohi, Amar Singh and Shakti Kumar,
“ANN Based Framework for Energy Efficient Routing
In Multi-Hop WSNs”. International Journal of
Advanced Research in Computer Science, Vol. 8, No.5,
2017.
[16] R. Sharma, B.S Sohi, “A Comparative Study on MAC
Protocols for Wireless Sensor Networks on Energy
Reduction”. International Journal of Computer Science
and Information Security, 15(11), 2017, pp 35–40.
[17] H. Aydin, R. Melhem, D. Mosse, and P. Mejia-Alvarez,
"Power-aware scheduling for periodic real-time tasks,"
IEEE Trans. on Computers, vol. 53, no. 5, pp. 584-600,
2004.
[18] S. Reda, R. Cochran, and A. K. Coskun, “Adaptive
power capping for servers with multi-threaded
workloads,” International Symposium on
Microarchitecture (MICRO ‘12), Vol. 32, No. 5, Aug.
2012, pp. 64-75.
[19] C. O. Diaz, M. Guzek, J. E. Pecero, P. Bouvry, and S. U.
Khan, “Scalable and energy-efficient scheduling
techniques for large-scale systems,” International Conference on Computer and Information Technology (CIT ‘11), Sept. 2011, pp. 641-647.
[20] S. U. Khan and I. Ahmad, “A cooperative game
theoretical technique for joint optimization of energy
consumption and response time in computational grids,”
IEEE Transactions on Parallel and Distributed Systems,
Vol. 20, No. 3, Mar. 2009, pp. 346-360.
[21] S. U. Khan and N. Min-Allah, “A goal programming
based energy efficient resource allocation in data
centers,” Journal of Supercomputing, Vol. 61, No. 3,
Sept. 2012, pp. 502-519.
[22] P. Lindberg, J. Leingang, D. Lysaker, K. Bilal, S. U.
Khan, P. Bouvry, N. Ghani, N. Min-Allah, and J. Li,
“Comparison and analysis of greedy energy-efficient
scheduling algorithms for computational grids,” in
Energy Aware Distributed Computing Systems, A. Y.
Zomaya and Y.-C. Lee, Eds., John Wiley & Sons,
Hoboken, NJ, USA, 2012, ISBN 978-0-470-90875-4,
Chapter 7.
[23] W. Dargie, "Dynamic power management in wireless
sensor networks: State-of-the-art," Sensors Journal,
IEEE, vol. 12, no. 5, pp. 1518-1528, may 2012.
[24] G. L. Valentini, W. Lassonde, S. U. Khan, N. Min-
Allah, S. A. Madani, J. Li, L. Zhang, L. Wang, N. Ghani,
J. Kolodziej, H. Li, A. Y. Zomaya, C.-Z. Xu, P. Balaji,
A. Vishnu, F. Pinel, J. E. Pecero, D. Kliazovich, and P.
Bouvry, “An overview of energy efficiency techniques
in cluster computing systems,” Cluster Computing, Vol.
16, No. 1, Mar. 2013, pp. 3-15.
[25] S. Zeadally, S. U. Khan, and N. Chilamkurti, “Energy
efficient networking: past, present, and future,” Journal of Supercomputing, Vol. 62, No. 3, Dec. 2012, pp.
1093-1118.
[26] X. Jin and S. Goto, “Hilbert transform-based workload
prediction and dynamic frequency scaling for power
efficient video encoding,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Vol. 31, No.5, May 2012, pp. 649-661.
[27] U. Tietze and C. Schenk, Electronic Circuits: Handbook
for Design and Application. Secaucus, NJ, USA:
Springer-Verlag New York, Inc., 2007.