## 1 Context and Motivations  
Wireless sensor networks consist of a large number of wireless sensor nodes that organize themselves into multi-hop radio networks. Sensor nodes are able to monitor a wide variety of physical parameters such as temperature, humidity, light, radiation, noise, _etc_. These sensor nodes have a low cost, small size and wireless data transfer capability. Hence, sensor networks are expected to find widespread use in applications such as environment protection, health monitoring, diagnosis help in maintenance applications, traffic monitoring on freeways or urban street intersections, seismic data-gathering. The sensor nodes are typically equipped by power-constrained batteries, which are often difficult, expensive and even impossible to be replaced once the nodes are deployed. Therefore, energy awareness becomes the key research challenge for sensor network protocols. In fact, several researchers have addressed energy conservation aiming at maximizing the network lifetime. The energy consumed by a node depends on its state. We distinguish four states: _(1) transmit, (2) receive, (3) idle_ when the node keeps listening the medium even when no messages are being transmitted and finally _(4) sleep_, where the radio module is switched off: no communication is possible. Table 1 reports the power used in each state for both IEEE 802.11 and IEEE 802.15.4 nodes. We can refine the receive state as follows:  
* _overhearing_: when a sender transmits a packet, all its neighbors will receive this packet even if it is intended for only one of them. Thus, in the overhearing state, any one hop neighbor of the sender that is not the destination will dissipate energy;
* _interference_: each node located between transmitter range and interference range receives the packet but can not decode it;  
More generally, energy efficient techniques tend to minimize the energy wasted in useless states from the application point of view such as idle listening, overhearing, interference, collision. Consequently, these techniques increase the network lifetime and improve energy efficiency. We can classify these techniques into four classes:  
* _energy-aware routing protocols_ select routes that minimize the energy consumed by an end-to-end transmission or visit nodes with high residual energy;
* _node activity scheduling algorithms_, whose objective is to turn off the sensor radio when it does neither transmit nor receive data; \begin{table}
\begin{tabular}{c c c} \hline \hline State & \multicolumn{2}{c}{Power (Watts)} \\ \cline{2-3}  & IEEE 802.11 & IEEE 802.15.4 \\ \hline Transmit & 1.3 & 0.1404 \\ Receive & 0.9 & 0.1404 \\ Idle & 0.74 & 0.0018 \\ Sleep & 0.047 & 0.000018 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Power value in each radio state. * _mechanisms to reduce the amount of data transferred_ like data aggregation, because the energy consumed depends on the data size;
* _topology control methods_ tuning node transmission power. We now focus on energy consumption in wireless _ad hoc_ and sensor networks. More precisely, we quantify the energy dissipated in transmitting, receiving, overhearing, idle listening and interference during network lifetime. The network lifetime is defined as the time of the first sensor node failure. The simulation parameters are given in Table 2. \begin{table}
\begin{tabular}{c c c} \hline  & Simulation parameter & Value \\ \hline Configuration & Number of nodes & 50–200 \\  & Density & 10 \\  & Bandwith & 2 Mbps \\  & Transmission range & 250 m \\ \hline Energy & Initial energy & 50 Joules \\  & Transmit & 1.3 Watt \\  & Receive & 0.9 Watt \\  & Idle & 0.74 Watt \\  & Sleep & 0.047 Watt \\ \hline Traffic & Number of flows & 30 \\  & Throughput & 16 Kbps \\  & Packet size & 512 bytes \\ \hline Routing & Hello period & 2 s \\  & TC period & 5 s \\ \hline \end{tabular}
\end{table} 
Table 2: Simulation parameters. Figure 1: Distribution of node energy consumption without the sleeping state.