# Survey on Power-Aware Optimization Solutions for MANETs
## 3 Analysis of Power-Aware Optimization Solutions in MANETs
### Transmission Power Control-Based Routing Protocols
Nevertheless, in EPAR the amount of energy used for the route process and the amount of remaining energy at each relay node are taken into consideration. [PERSON] et al. [184] proposed the Minimal Energy Consumption with Optimized Routing (MECOR) protocol that focuses on the use of energy consumption as the main performance metric for routing decisions. From another perspective, [PERSON] et al. [185] proposed an energy-aware routing protocol (called Double Metric), that obtains increased effectiveness by combining QoS and energy-efficiency in determining the best routing path to be selected. This approach ensures a balance between the robustness of routing and the energy efficiency of routing. The advantage of this energy-aware routing protocol method is that it is very efficient in obtaining the routing path with a minimal cost value. However, the main drawback of this protocol is that, if not combined with another energy-efficient approach, it will result in the overuse of limited energy resources from the battery of the intermediate nodes, thus resulting in network failure. [PERSON] et al. [186] examined the packet delivery ratio and energy consumption under a multicast scenario by taking into account the transmission power control for each node. In their multicast scenario, a packet from the source node can be delivered to up to \(f\) different relay nodes. Each of the \(d\) destination nodes may receive the packet from these relay nodes (or the source node) before the packet lifetime \(\tau\) expires. It can be said that, in this scenario, we have a redundancy factor \(f\), multicast scale \(d\), packet lifetime \(\tau\), and a power control parameter \(w\) for packet routing. The power control parameter \(w\) is fixed and equal for all nodes. Initially, the authors assumed a general two-hop relay RT (_f_, \(d\), \(\tau\), _w_) algorithm with redundancy factor \(f\), multicast scale \(d\), packet lifetime \(\tau\) and power control parameter \(w\) for packet routing. Next, they developed a Markov chain framework to depict the packet propagation process under this two-hop relay algorithm. Using this framework, they derived two analytical expressions for PDR and energy consumption. Finally, they validated their theoretical analysis and investigated how the abovementioned network parameters affect the PDR and energy consumption performance. Finally, [PERSON] and [PERSON] [187] proposed the Multi Criteria Decision Making (MCDM) method combined with Intuitionistic Fuzzy Soft Set (IFSS) method. The authors placed special emphasis on the efficiency of utilizing energy capacity as part of route cost calculation by considering the rapid changes that occur in the identified routes. The use of the MCDM method, combined with the IFSS method, can calculate the cost of changing network routes efficiently and accurately. Table 2 summarizes the previous schemes and methods described. Subsequently, we discuss cross-layer optimization-based routing approaches, which are based on effective cross-layer designs (CLDs) and provide better network management in terms of QoS, and energy consumption.