# A Survey on an Energy-Efficient and Energy-Balanced Routing Protocol for Wireless Sensor Networks
## 4 Overview of Energy Consumption in WSNs
### SNs Energy Dissipation Issues  
Figure 4 depicts a typical WSN scenario where all the SNs are heterogeneous and static after their deployment. We also assume that the coordinates of the SNs and BS are known, and the residual energy of the SNs is as defined in the figure. From the figure, assume that \(SN_{5}\) attempts to transmit a \(q\) bit message to the BS at its allocated time-division multiple-access (TDMA) schedule. Note that the TDMA schedule [49] makes certain that there are no data collisions during the network activities. In such a way, the TDMA schedule conserves energy by allowing SNs to sleep all the time except during the node's transmission time. The \(SN_{5}\) can convey the \(q\) bit message to the BS either by single-hop or multi-hop communication. In single-hop communication, \(SN_{5}\) transmits the \(q\) bit message to the BS directly without using any relay node. As shown in the figure, we assume that the distance \(d\) between \(SN_{5}\) and the BS computed in the form of a distance metric is considerably large. Therefore, applying Equation (4) means that \(SN_{5}\) will consume a lot of energy to successfully transfer the \(q\) bit message to the BS. This forms a major disadvantage with single-hop communication. However, this can be advantageous in scenarios where the SN is very close to the BS. For example, this mode of communication will be advantageous if \(SN_{8}\) attempts to convey its \(q\) bit message to the BS. Nevertheless, a major characteristic of WSNs is that the participating SNs are randomly placed in the sensor field, which means that some SNs will be at a huge distance from the BS. The SNs that are at a large distance from the BS will easily deplete their battery energy using single-hop communication to convey their messages which subsequently hampers the network functionality. In an attempt to reduce the energy consumed by the SNs that are at a large distance from the BS, some energy-balanced routing protocols such as the LEACH (low-energy adaptive clustering hierarchy) protocol [50] clustered the WSN and rotated the duty of the CH. This method is somewhat useful because the distant nCH nodes do not need to send their sensed information to the BS directly. The nCH nodes send their sensed information to their respective CH with less transmission power in most cases as compared to sending the sensed information to the BS directly. This clustering technique,  
Figure 4: Typical WSN scenario, where \(r=0\). Figure 3: Simplified WSN energy dissipation model. however, does not completely solve the distance problem associated with single-hop communication because the CHs convey the message from their cluster members directly to the BS. The placement of these SNs which include the CH is very unpredictable, and numerous works are ongoing to proffer a solution to the node placement problem with WSNs [51; 52]. Therefore, in a scenario where the CH(s) is at a large distance from the BS, the CH nodes(s) will dissipate a lot of energy to transfer the message from its cluster members to the BS. These CH(s) can easily deplete their energy completely, thereby leading to the untimely partitioning of the network. As a result of this distance problem associated with single-hop communication, recent research work on WSNs makes use of the multi-hop communication method. With multi-hop communication, the source SN transmits the \(q\) bit message to the BS through one or more relay nodes. In such a way, researchers envisaged that the energy dissipated by the SNs with large distances from the BS will be minimised in comparison to the single-hop communication method. The multi-hop communication method is used in different energy-efficient and energy-balanced routing protocols in order to optimize the energy consumption by the SNs in the network. Most of the energy-efficient and energy-balanced routing protocols in literature that are based on multi-hop communication can be categorized under (1) the clustering technique and (2) load-balanced tree technique.