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Enhancing Energy Efficiency at Multiple Layers in
Wireless Sensor Networks
By
Mr. Zeeshan Abbas
Registration Number: CIIT/FA11-REE-007/ISB
MS Thesis
In
Electrical Engineering
COMSATS Institute of Information Technology
Islamabad – Pakistan
FALL, 2012
ii
Enhancing Energy Efficiency at Multiple Layers in
Wireless Sensor Networks
A Thesis presented to
COMSATS Institute of Information Technology
In partial fulfillment
of the requirement for the degree of
MS (Electrical Engineering)
By
Mr. Zeeshan Abbas
CIIT/FA11-REE-007/ISB
Fall, 2012
iii
Enhancing Energy Efficiency at Multiple Layers in
Wireless Sensor Networks
A Graduate Thesis submitted to Department of Electrical Engineering as
partial fulfillment of the requirement for the award of Degree of M. S.
(Electrical Engineering).
Name
Registration Number
Mr. Zeeshan Abbas
CIIT/FA11-REE-007/ISB
Supervisor:
Dr. Nadeem Javaid,
Assistant Professor,
Center for Advanced Studies in Telecommunications (CAST),
COMSATS Institute of Information Technology (CIIT),
Islamabad Campus,
December, 2012
iv
Final Approval
This thesis titled
Enhancing Energy Efficiency at Multiple Layers in
Wireless Sensor Networks
By
Mr. Zeeshan Abbas
CIIT/FA11-REE-007/ISB
has been approved
for the COMSATS Institute of Information Technology, Islamabad
External Examiner: __________________________________
(To be decided)
Supervisor: ________________________
Dr. Nadeem Javaid /Assistant professor,
Center for Advanced Studies in Telecommunications (CAST),
CIIT, Islamabad.
Head of Department:________________________
Dr. Raja Ali Riaz / Associate professor,
Department of Electrical Engineering,
CIIT, Islamabad.
v
Declaration
I Mr. Zeeshan Abbas, CIIT/FA11-REE-007/ISB herebyxdeclare that I
havexproduced the workxpresented inxthis thesis, duringxthe scheduledxperiod of
study. I also declare that I havexnot taken anyxmaterial from anyxsource
exceptxreferred toxwherever due that amountxof plagiarism isxwithin
acceptablexrange. If a violationxof HEC rulesxon research hasxoccurred in
thisxthesis, I shall be liablexto punishablexaction under the plagiarismxrules of the
HEC.
Date: ________________
________________
Mr. Zeeshan Abbas
CIIT/FA11-REE-007/ISB
vi
Certificate
It is certified that Mr. Zeeshan Abbas, CIIT/FA11-REE-007/ISB has carried out
all the work related to this thesis under my supervision at the Department of
Electrical Engineering, COMSATS Institute of Information Technology,
Islamabad and the work fulfills the requirements for the award of MS degree.
Date: _________________
Supervisor:____________________
Dr. Nadeem Javaid /Assistant professor,
Center for Advanced Studies in Telecommunications (CAST),
CIIT, Islamabad.
____________________________
Head of Department:
Dr. Raja Ali Riaz/Associate Professor,
Department of Electrical Engineering,
CIIT, Islamabad.
vii
DEDICATION
Dedicated to my parents.
viii
ACKNOWLEDGMENT
I am heartily grateful to my supervisor, Dr. Nadeem Javaid, whose patient encouragement,
guidance and insightful criticism from the beginning to the final level enabled me have a deep
understanding of the thesis.
Lastly, I offer my profound regard and blessing to everyone who supported me in any respect
during the completion of my thesis especially my friends in every way offered much assistance
before, during and at completion stage of this thesis work.
Mr. Zeeshan Abbas
CIIT/FA11-REE-007/ISB
ix
Abbreviations and Notations
WSN
Wireless s Sensor Network
ECC
Error Control Code
Eb/N0
Bit Energy per Noise Power Spectral Density
ACK
Acknowledgment
ARQ
Automatic Repeat Request
FEC
Forward Error Correction
Critical Distance
,
Energy Required for Transmission Un-coded
Data
,
Energy Required for Transmission of Coded
Data
Energy Saving
Transmission energy
Energy Consumed by Transmit Amplifier
Energy Consumed for Processing Data
Loss of Energy during Multi-hop
Communication
Loss of Energy during Single-hop
Communication
D
Distance Between Each Node
SNR
Signal Power to Noise Power
Η
Spectral Efficiency
F
Frequency
RNF
Receiver Noise Figure
R
Data Rate
B
Bandwidth
Λ
Wavelength
K
Boltzman Constant
M
Noise Proportionality Constant
Pt
Transmitter Power
PL
Path Loss
ECCgain
Coding Gain
RS
Reed Solomon
CC-Hard
decision
Convoloutional Code Hard decision
CC-Soft
decision
Convoloutional Code Soft decision
BER
Bit Error Rate
IEEE802.15.4
WSN Standard
x
List of Publications
[1] Z. Abbas, N. Javaid, M. A. Khan, U. Qasim, Z. A. Khan, “Simulation Analysis
of IEEE 802.15.4 Non Beacon Mode at Varying Data Rates’’, published in 7th
International Conference on Broadband and Wireless Computing, Communication
and Applications (BWCCA-2012), Victoria, Canada, 2012.
[2] Z. Abbas, N. Javaid, “M-ATTEMPT: Proposing and Validating a New
Energy-Efficient Routing Protocol for Wireless Body Area Sensor Networks”,
submitted in 10th IEEE International Conference on Wireless On-demand Network Systems
and Services (WONS'13), March 18-20, 2013, Banff, Canada.
[3] Z. Abbas, N. Javaid, “EAPESS: An Adaptive Transmission Scheme in WSNs”
submitted in 4th IEEE International Conference on Ambient Systems, Networks and
Technologies (ANT-13) June 25-28, 2013, Halifax, Nova Scotia, Canada.
xi
ABSTRACT
Reduced energy consumption in sensor nodes is one of the major challenge in Wireless Sensor
Networks (WSN's) deployments. In this regard, Error Control Coding (ECC) is one of techniques
used for energy optimization in WSN's. Similarly, Critical distance is another term being used
for energy efficiency, when used with ECC provides better results of energy saving. In my thesis,
I have used three different critical distance values against different coding gains for sake of
energy saving. If distance lies below critical distance values then particular encoders are selected
with respect to their particular coding gains. Coding gains are used for critical distances
estimation of all encoders. This adaptive encoder and transmit power selection scheme with
respect to their coding gain results in a significant energy saving in WSN's environment.
Simulations provide better results of energy saving achieved by using this adaptive scheme.
In my work, i have also presented an energy efficient routing algorithm for heterogeneous
Wireless Body Area Sensor Networks (WBASNs). A prototype is defined for employing
heterogeneous sensors on human body. Direct communication is used for real-time traffic
(critical data) and on-demand data while Multi-hop communication is used for normal data
delivery in this proposed routing algorithm. One of the prime challenges in WBASNs, is sensing
of heat generated by implanted sensor nodes. The proposed routing algorithm is thermal-aware
which senses the link Hot-spot and routes the data away from these links. Continuous mobility of
human body causes disconnection between previous established links. So, mobility support and
energy-management is introduced to overcome the problem. Linear Programming (LP) model for
maximum information extraction and minimum energy consumption is defined in this study.
MATLAB simulations of proposed routing algorithm are performed for lifetime and reliability in
comparison with Multi-hop communication. The results show that the proposed routing
algorithm has less energy consumption and more reliable as compared to Multi-hop
communication.
42
Appendix:
1: Error Control Coding (ECC): Method in which redundancies introduced into data to be
transmitted and transmitter enables receiver to detect or correct some errors.
2: Critical Distance: Distance at which decoder energy consumption becomes equal to transmit
energy saving.
3: Coding Gain: Ability of encoder to provide better BER over noisy channel for same signal to
noise ratio as compared to an un-coded systems.
4: Bit Error Rate: Item Ratio of bit errors in received bits of data to total transferred bits in unit
time is called bit error rate.
5: Signal to Noise Ratio: Ratio of desired signal level to back ground noise is called signal to
noise ratio.
6: Decoding: In general, given any (n; k ) linear block code, there is a (n k)*n parity check
matrix H such that r is a codeword if and only if rHT = 0. If G is of the form [IP], then H is of the
form [- PT I]
7: Code Rate: R=K/n defines code rate of a code. n defines length of a code word and k is the
number of data bits in a code word.
8: Convolutional Codes: In convolutional codes each block of n coded bits depends not only on
the K data bits but also on the previous data bits, and that is done by introducing memories.
9: Automatic Repeat Request: Error correction method an ack is sent after successful reception
of data, if no ack received in specific time then data is retransmitted.
10: Forward Error Correction: Redundant bits are sent with data by using ECC technique.
Redundancy allows receiver to correct limited number of errors and correction is made without
retransmission.
11: Required Transmit Power: Minimum transmit power at which data can be successfully
transmitted without error.
12: Noise Power Spectral Density: Noise power per unit bandwidth.
13: Spectral Efficiency: Info that can be transmitted over given bandwidth.
14: Homogeneous Sensor Network: Network in which all sensor nodes are having same energy
levels.
43
15: Heterogeneous Sensor Network: Network in which all sensor nodes are having different
energy levels.
16: Multi-hop Communication: Communication in which nodes can send their data to sink
through multiple other nodes.
17: Single-hop Communication: Communication in which nodes can send their data to sink
directly without sending to another node.