# 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
In the multi-hop clustering technique, the SNs transmit their sensed information to their respective CHs using multi-hop communication. Similarly, the CH sends the aggregated data to the BS via relay nodes (the relay node can either be a CH or nCH) or directly (single-hop communication) depending on the CH distance to the BS. The load-balanced tree technique finds the route from the source SN to the BS that balances the energy consumption in the network. The load-balanced tree technique can be in the form of a multipath algorithm or a single-path algorithm. Nonetheless, these multi-hop communication methods have not completely solved the energy consumption issues with WSNs. A major challenge with these multi-hop communication methods is the trade-off between finding the most distance efficient path to the BS and the energy-efficient and/or energy-balanced path to the BS. For example, as illustrated in Figure 5a, we assume that the shortest path from \(SN_{5}\) to the BS in Figure 4 is through \(SN_{28}\), \(SN_{15}\), \(SN_{21}\), \(SN_{3}\), and \(SN_{11}\). As depicted, \(SN_{21}\) has depleted more of its energy in comparison to the other SNs in the network. This simply means that \(SN_{21}\) will die easily if used as part of the relay node when transmitting the message from \(SN_{5}\) to the BS. In such a scenario, we can say that this distance efficient route to the BS from \(SN_{5}\) is not the most \"energy-balanced\" route to the BS from \(SN_{5}\). Although, as shown in Equations (4)-(6), the distance between SNs or a SN and the BS plays a key role in minimizing the energy consumption by the SNs; in this example, the distance efficient route does not offer a balance in the energy dissipated by the SNs in the network. Thus, finding the most distance efficient route to BS that optimizes the energy consumption by SNs can be a NP-hard problem because of network requirements and formulations. Figure 5: Multi-hop communication method. (**a**) Shortest path from \(SN_{5}\) to the BS; (**b**) Energy-efficient route from \(SN_{5}\) to the BS. Moreover, some energy-efficient routing protocols use the current energy level (residual energy) of the SNs in the network to find the most energy-efficient route(s) to the BS from the source node. The residual energy of SNs is a key design decision variable used by researchers to develop routing protocols for WSNs. Some of these algorithms select the SNs with high residual energy to form the relay node's chain from the source node to the BS. For example, let us assume that the energy-efficient route from \(SN_{5}\) to the BS in Figure 4 based on the energy level of the SNs is as represented in Figure 5b. These SNs acting as the relay nodes have high residual energy and can easily convey the message from \(SN_{5}\) to the BS for many data transmission rounds before they completely deplete their energy. This energy-efficient route depicted in Figure 5b will definitely solve the problem associated with the distance efficient route of Figure 5a because the participating nodes can go many data transmission rounds before they deplete their energy completely. However, using these SNs with very high residual energy does not necessarily balance the energy consumption in the network. In this example, we assume that the sensed information from \(SN_{5}\) is transmitted over a longer distance as compared to the illustration in Figure 5a. This means that the total energy consumed using this energy-efficient route depicted in Figure 5b will be more than the total energy dissipated using the shortest path example of Figure 5a with respect to Equations (4)-(6). In such a scenario, we can say that this energy-efficient route to the BS from \(SN_{5}\) is not the most \"energy-balanced\" route despite the message being transmitted by relay nodes with high residual energy. Therefore, there must be a route from \(SN_{5}\) to the BS that balances the energy dissipated by the SNs and the total energy dissipated in the network.