الفهرس 
Abstract
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Abstract
Wireless Sensor Network (WSN) technology has gained significant importance due to its
potential support for a wide range of applications. Most of the WSN applications consist of a large
number of distributed nodes that work together to achieve common goals. Running a large number of
nodes requires an efficient mechanism to bring them all together in order to form a multi-hop wireless
network that can accomplish some specific tasks. Even with recent developments made in WSN
technology, numbers of important challenges still stand as vulnerabilities for WSNs, including
energy waste sources, synchronization leaks, low network capacity and self-configuration difficulties.
However, energy efficiency remains the priority challenging problem due to the scarce energy
resources available in sensor nodes.. In this regard, energy modeling is an important issue in
designing and implementing of these networks, which help the designers to optimize the energy
consumption in WSN nodes.
This thesis presents advanced research work carried out in the context of saving energy
whilst achieving the desired network performance. Firstly, the thesis contributes by proposing an
energy consumption model for WSNs considering the physical layer by determining the energy
consumed per payload bit transferred without error over correlated or uncorrelated random channels.
Secondly, this thesis proposed an energy consumption model for WSNs considering the MAC layer
by determining the energy consumed per payload bit transferred without error over correlated or
uncorrelated random channels. These energy models have been implemented and evaluated using real
system and NS-2 simulator. Results have shown that the proposed models are closely matched to real
system with relative error up to 5.8%.
The proposed models are used to optimize the transmitted power and modulation level. For
transmitted power, results show that a single optimal transmitted power exists for each type of wireless
channels. In addition, it depends on the packet size, modulation size and channel statistics.
Furthermore, we derive analytic expressions for the optimal transmitted power at which the energy
consumption is minimum for AWGN and Rayleigh channels for different modulation schemes. For
modulation level, we investigate the energy saving gained from optimizing the constellation size to
minimize energy consumption with a target symbol error rate. We found that the optimal modulation
level increases as the target error probability increases. Finally, we derive analytic expressions for the
optimal constellation size for QAM modulation at target symbol error probability.