الفهرس 
Chapter 1 IntroductionOnly 14 pages are availabe for public view
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Abstract
A Wireless Sensor Network (WSN) consists of a number of sensor nodes that
are randomly deployed, and it transforms a physical data into a form that would
make it easier for the user to understand. The main challenge in the design of
WSNs is the limited battery power of the sensor nodes and the difficulty of
replacing or recharging these batteries due to the nature of the monitored field.
The direct approach to collect data from sensor nodes is that each sensor node
transmits the data directly to the Base Station (BS). However, this approach
consumes a lot of energy to transmit data from each sensor node to the BS. Thus,
nodes die very quickly, and as a result, they reduce the network lifetime.
Therefore, as few transmissions as possible are desired for efficient energy
utilization.
Firstly, a modification of the Low Energy Adaptive Clustering Hierarchy
(LEACH) protocol is presented based on compressive sensing to reduce the
amount of power by decreasing the size of transmitted data. Furthermore, a
proposed protocol, namely Adaptive Soft Thresholding based Energy Efficient
sensor Network (ASTEEN) is presented to reduce the amount of energy in WSNs
based on an adaptive soft thresholding strategy that takes the importance of sensed
data into consideration. The Peak-to-Average Ratio Reduction (PAPR) problem is
considered in this thesis to reduce transmission power. Several non-linear
companding techniques are presented and compared for this purpose. Moreover,
the routing strategy in sensor networks is considered in an efficient treatment.
A Wireless Sensor Network (WSN) consists of a number of sensor nodes that
are randomly deployed, and it transforms a physical data into a form that would
make it easier for the user to understand. The main challenge in the design of
WSNs is the limited battery power of the sensor nodes and the difficulty of
replacing or recharging these batteries due to the nature of the monitored field.
The direct approach to collect data from sensor nodes is that each sensor node
transmits the data directly to the Base Station (BS). However, this approach
consumes a lot of energy to transmit data from each sensor node to the BS. Thus,
nodes die very quickly, and as a result, they reduce the network lifetime.
Therefore, as few transmissions as possible are desired for efficient energy
utilization.
Firstly, a modification of the Low Energy Adaptive Clustering Hierarchy
(LEACH) protocol is presented based on compressive sensing to reduce the
amount of power by decreasing the size of transmitted data. Furthermore, a
proposed protocol, namely Adaptive Soft Thresholding based Energy Efficient
sensor Network (ASTEEN) is presented to reduce the amount of energy in WSNs
based on an adaptive soft thresholding strategy that takes the importance of sensed
data into consideration. The Peak-to-Average Ratio Reduction (PAPR) problem is
considered in this thesis to reduce transmission power. Several non-linear
companding techniques are presented and compared for this purpose. Moreover,
the routing strategy in sensor networks is considered in an efficient treatment.
A Wireless Sensor Network (WSN) consists of a number of sensor nodes that
are randomly deployed, and it transforms a physical data into a form that would
make it easier for the user to understand. The main challenge in the design of
WSNs is the limited battery power of the sensor nodes and the difficulty of
replacing or recharging these batteries due to the nature of the monitored field.
The direct approach to collect data from sensor nodes is that each sensor node
transmits the data directly to the Base Station (BS). However, this approach
consumes a lot of energy to transmit data from each sensor node to the BS. Thus,
nodes die very quickly, and as a result, they reduce the network lifetime.
Therefore, as few transmissions as possible are desired for efficient energy
utilization.
Firstly, a modification of the Low Energy Adaptive Clustering Hierarchy
(LEACH) protocol is presented based on compressive sensing to reduce the
amount of power by decreasing the size of transmitted data. Furthermore, a
proposed protocol, namely Adaptive Soft Thresholding based Energy Efficient
sensor Network (ASTEEN) is presented to reduce the amount of energy in WSNs
based on an adaptive soft thresholding strategy that takes the importance of sensed
data into consideration. The Peak-to-Average Ratio Reduction (PAPR) problem is
considered in this thesis to reduce transmission power. Several non-linear
companding techniques are presented and compared for this purpose. Moreover,
the routing strategy in sensor networks is considered in an efficient treatment.
A Wireless Sensor Network (WSN) consists of a number of sensor nodes that
are randomly deployed, and it transforms a physical data into a form that would
make it easier for the user to understand. The main challenge in the design of
WSNs is the limited battery power of the sensor nodes and the difficulty of
replacing or recharging these batteries due to the nature of the monitored field.
The direct approach to collect data from sensor nodes is that each sensor node
transmits the data directly to the Base Station (BS). However, this approach
consumes a lot of energy to transmit data from each sensor node to the BS. Thus,
nodes die very quickly, and as a result, they reduce the network lifetime.
Therefore, as few transmissions as possible are desired for efficient energy
utilization.
Firstly, a modification of the Low Energy Adaptive Clustering Hierarchy
(LEACH) protocol is presented based on compressive sensing to reduce the
amount of power by decreasing the size of transmitted data. Furthermore, a
proposed protocol, namely Adaptive Soft Thresholding based Energy Efficient
sensor Network (ASTEEN) is presented to reduce the amount of energy in WSNs
based on an adaptive soft thresholding strategy that takes the importance of sensed
data into consideration. The Peak-to-Average Ratio Reduction (PAPR) problem is
considered in this thesis to reduce transmission power. Several non-linear
companding techniques are presented and compared for this purpose. Moreover,
the routing strategy in sensor networks is considered in an efficient treatment.