X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/ThesisAli.git/blobdiff_plain/b23110f2239dfafa18be5c27d331fa589992136c..a1ce01d485446da92069b5d68b1ed880ee49f69b:/CHAPITRE_01.tex?ds=inline diff --git a/CHAPITRE_01.tex b/CHAPITRE_01.tex index 5343c05..a70a010 100644 --- a/CHAPITRE_01.tex +++ b/CHAPITRE_01.tex @@ -11,7 +11,7 @@ \section{Introduction} \label{ch1:sec:01} -The wireless networking has been receiving more attention and fast growth in the last decade. The growing demand for the use of wireless applications and emerging the wireless devices such as portable computers, cellular phones, and personal digital assistants (PDAs) have been led to develop different infrastructures of wireless networks. The wireless networks can be classified into two classes based on network architecture: Infrastructure-based networks that consists of a fixed network structure such as cellular networks and wireless local-area networks +The wireless networking has been receiving more attention and fast growth in the last decade. The growing demand for the use of wireless applications and emerging the wireless devices such as portable computers, cellular phones, and personal digital assistants (PDAs) have been led to develop different infrastructures of wireless networks. The wireless networks can be classified into two classes based on network architecture~\cite{ref154,ref155}: Infrastructure-based networks that consists of a fixed network structure such as cellular networks and wireless local-area networks (WLANs); and Infrastructureless networks that constructed dynamically by the cooperation of the wireless nodes in the network, where each node capable of sending the packets and taking the decision based on the network status. Examples for such type of networks include mobile ad hoc networks and wireless sensor networks. Figure~\ref{WNT} shows the taxonomy of wireless networks. \begin{figure}[h!] @@ -27,7 +27,9 @@ In recent years, there is increasing interest in Wireless Sensor Networks (WSNs) \section{Wireless Sensor Network Architecture} \label{ch1:sec:02} -In a typical WSN architecture, the basic element is a typical wireless sensor node that composed of four major units~\cite{ref17,ref18}: sensing unit, computation unit, communication unit, and power unit. In addition, there are three optional units, which can be combined with the sensor node such as: localization system, mobilizer, and power generator. Figure~\ref{twsn} shows the components of a typical wireless sensor node~\cite{ref17}. +A typical WSN architecture consists of a set of a typical wireless sensor nodes, which are capable of sensing the physical phenomenon around it such as fire in the forest (see~figure~\ref{wsn}), and then send the sensed data to a controller node called a sink. One or more sink in WSN are responsible for collecting and processing the sensed data by the wireless sensors, and then send it through the Internet to the end user. + +In those WSN architecture, the basic element is a typical wireless sensor node that composed of four major units~\cite{ref17,ref18}: sensing unit, computation unit, communication unit, and power unit. In addition, there are three optional units, which can be combined with the sensor node such as: localization system, mobilizer, and power generator. Figure~\ref{twsn} shows the components of a typical wireless sensor node~\cite{ref17}. \begin{figure}[h!] \centering @@ -55,9 +57,6 @@ Furthermore, additional components can be incorporated into wireless sensor node \item \textbf{Power Generator:} Several WSN applications need to operate for a longer time, so it is essential to equip the wireless sensor node with additional power source in order to prolong the network lifetime. The better energy source to generate the power for outdoor applications is a solar cells. An another power harvesting mechanisims~\cite{ref20,ref21} for thermal, motion, vibration, micro water flow, Biological, pressure gradients, and electromagnetic radiation energy harvesting can be used that yield increasing power output to extend the network lifetime. \end{enumerate} -The TinyOS has been used as an operating system in wireless sensor node. It is developed by the university of California, Berkeley and designed to work on platforms with limited storage and processing power. - -A typical WSN architecture consists of a set of a typical wireless sensor nodes, which are capable of sensing the phenomenon of interest around it such as fire in the forest (see~figure~\ref{wsn}) and then send the sensed data to a controller node called a sink. One or more sink in WSN are responsible for collecting and processing the sensed data by the wireless sensors, and then send it through the Internet to the end user. \begin{figure}[h!] \centering \includegraphics[scale=0.9]{Figures/ch1/wsn.jpg} @@ -65,6 +64,8 @@ A typical WSN architecture consists of a set of a typical wireless sensor nodes, \label{wsn} \end{figure} +The TinyOS has been used as an operating system in wireless sensor node. It is developed by the university of California, Berkeley and designed to work on platforms with limited storage and processing power. + \section{Types of Wireless Sensor Networks} \label{ch1:sec:03} @@ -407,6 +408,7 @@ In this section, two energy consumption models are explained. The first model ca \subsection{Radio Energy Dissipation Model} +\label{ch1:sec9:subsec1} Since the communication unit is the most energy-consuming part inside the sensor node, and accordingly there are many authors used the radio energy dissipation model that proposed in~\cite{ref109,ref110} as energy consumption model during the simulation and evaluation of their works in WSNs. Figure~\ref{RDM} shows the radio energy dissipation model. \begin{figure}[h!] \centering @@ -441,6 +443,7 @@ The radio energy dissipation model have been considered only the energy consumed \subsection{Our Energy Consumption Model} +\label{ch1:sec9:subsec2} In this dissertation, the coverage protocols have been used an energy consumption model proposed by~\cite{ref111} and based on \cite{ref112} with slight modifications. The energy consumption for sending/receiving the packets is added, whereas the part related to the sensing range is removed because we consider a fixed sensing range. For our energy consumption model, we refer to the sensor node Medusa~II which uses an Atmels AVR ATmega103L microcontroller~\cite{ref112}. The typical architecture of a sensor is composed of four subsystems: the MCU subsystem which is capable of computation, communication subsystem (radio) which is responsible for transmitting/receiving messages, the sensing subsystem that collects data, and the power supply which powers the complete sensor node \cite{ref112}. Each of the first three subsystems can be turned on or off depending on the current status of the sensor. Energy consumption @@ -476,7 +479,7 @@ COMPUTATION & on & on & on & 26.83 \\ \end{table} For the sake of simplicity we ignore the energy needed to turn on the radio, to start up the sensor node, to move from one status to another, etc. -Thus, when a sensor becomes active (i.e., it has already chosen its status), it can turn its radio off to save battery. The value of energy spent to send a 1-bit-content message is obtained by using the equation in ~\cite{ref112} to calculate the energy cost for transmitting messages and we propose the same +Thus, when a sensor becomes active (i.e., it has already chosen its status), it can turn its radio off to save battery. The value of energy spent to send a 1-bit-content message is obtained by using the equation in ~\cite{ref112} to calculate the energy cost for transmitting messages and we propose the same value for receiving the packets. The energy needed to send or receive a 1-bit packet is equal to $0.2575~mW$.