# A Survey on an Energy-Efficient and Energy-Balanced Routing Protocol for Wireless Sensor Networks
## 5 Taxonomy for Energy-Efficient and Energy-Balanced Routing Protocols
### Multi-Hop Communication Method
#### 5.1.1 Multi-Hop Clustering Technique
Moreover, the CH nodes close to the BS will consume more energy because they always have to participate in the relaying duties. On the other hand, since the CH nodes perform more duties in comparison to the nCH nodes, the lower tier nodes (nCH nodes) can be used to form the relay node's chain towards the BS. As shown in Table 3, this approach has not been used but we emphasised that this approach will reduce the burden of the CH nodes in relaying the message to the BS. Therefore, we assumed that this approach can be considered in designing multi-hop clustering routing protocols in the future. Moreover, some authors share the relaying duties between the two-tier nodes. Both the CH nodes and the nCH nodes can act as a relay node in transmitting the aggregated information towards the BS depending on the design decision variables used. This approach tends to prolong the network lifetime performance as compared to using only the CH nodes. However, if the design decision variables are not carefully specified in the clustering algorithm, the SNs acting as CH nodes might frequently participate in the relaying duties. Thus, this approach will suffer the same setback as using only the CH nodes. With regards to this, we grouped the studied clustering routing protocols that employ the multi-hop method during the inter-cluster communication phase based on the nodes performing the relaying duties toward the BS. As shown in Table 3, we grouped the relay nodes used during the inter-cluster communication phase under \"CHtoBS\". Finally, in Table 3, we grouped the studied multi-hop clustering routing protocols based on the solution types or algorithms used. Optimization plays a vital role in WSNs. Generally, an optimization problem comprises of the input decision variables, constraints, objective functions and the outputs. In most of the optimization problems associated with WSNs, these component parts can be merged with numerous dissimilar combinations resulting in different kinds of optimization problems. As such, there is no single algorithm that proffers a solution to the different optimization problems affiliated with WSNs [54]; this is with respect to the energy consumption issues with WSNs, where the major objective function is to minimise the energy consumption in the SNs in the network and the total energy in the network. We grouped the studied multi-hop clustering routing protocols based on optimization solution types or algorithms as shown in Table 3. As illustrated in Table 3, \"B\" stands for bio-inspired-based algorithms, \"E\" stands for evolutionary-based algorithms, \"G\" stands for game theory-based algorithms, \"H\" stands for heuristic-based algorithms, \"L\" stands for linear programming-based algorithms,\"M\" stands for meta-heuristic-based algorithms, and \"S\" stands for stochastic-based algorithms. \begin{table} \begin{tabular}{c} **Intra-Cluster** \\ **Communication** \\ **(Decision Variables)** \\ \end{tabular}