# Survey on Power-Aware Optimization Solutions for MANETs
## 3 Analysis of Power-Aware Optimization Solutions in MANETs
### Cross-Layer Optimization for Energy Conservation in MANETs
#### 3.8.2 Cross-Layer Designs for MANETs
Equations (3)-(5) calculate the average, minimum, and maximum receiver signal strength (RSS), correspondingly:  
\[A_{RSS}=\frac{\sum_{i=1}^{m}RSS_{i}}{n} \tag{3}\]  
\[A_{Min_{RSS}}=\frac{\sum_{i=1}^{Min_{node}}RSS_{i}}{Min_{node}},\text{ for }RSS_{i}<A_{RSS} \tag{4}\]\[A_{Max_{RSS}}=\frac{\sum_{i=1}^{Max_{node}}RSS_{i}}{Max_{node}},\text{ for }RSS_{i}>A_{RSS} \tag{5}\]  
where \(m\) is the sum of single-hop neighbor nodes of node \(X_{i}\) with \(RSS_{i}\) representing the sum of the RSS value of neighbor nodes. Each node determines the communication region by using these values. The RSS value is inversely proportional to the transmission distance. This means that a low value of RSS can cover a larger communication region and vice versa. [PERSON] et al. [49] presented a cross-layer multipath routing protocol for MANETs that is efficient and fault-tolerant in a diversity of application environments. The protocol is adaptive as it exploits those routes that are capable of providing more data rates with a lower packet loss ratio (PLR). The authors assume that MANETs are established for three types of applications: (1) simple; (2) multimedia; (3) applications with security requirements. A multimedia application needs such routes that have more bandwidth and minimum end-to-end delay. Taking into account the type of the application, the routing protocol chooses proper multipaths. For example, for a multimedia application, the proposed protocol selects two (or more than two) routes which are bandwidth-rich and have minimum delay from source to destination. Some important features of their protocol are as follows: (1) the APP layer defines the type of application; (2) the security module is working at the network layer; (3) bandwidth and end-to-end delay parameters are taken from the MAC layer. Their protocols were compared with other routing protocols (DSR, AODV, OLSR, CEDAR, PLQBR, QAODV, SAODV, and CSROR) using PDR, average delay, and routing overheads metrics with and without malicious nodes, and it was found to be efficient and fault-tolerant in most scenarios. [PERSON] et al. [199] implemented a cross-layer routing protocol for a hybrid MANET that uses a fuzzy-based mechanism for all layers by employing two input parameters: energy and mobility. This mechanism offers a better quality of network resources and enhanced network lifetime. It consists of a decision metric in each layer, based on QoS and Quality of Experience (QoE) to enhance network lifetime and energy efficiency. [PERSON] et al. [200] proposed and evaluated a cross-layer routing protocol, considering power control and rate adaptation by using a delay-based non-selfish cost function with a multi-agent Q-learning coordination mechanism. Simulation results showed that this protocol improves the average end-to-end latency and throughput with acceptable power consumption level. In the simulation experiments, various parameters were examined, such as node density, node mobility, traffic load, and the number of flows. [PERSON] and [PERSON] [201] considered the problem of adjusting the transmission power of the nodes to an optimal power level. They incorporated low power consumption strategies into the routing protocol through an upward information flow cross-layer model between the MAC layer, and the Network layer. They proposed a new energy-efficient CLD to AODV, called Cross-Layer Energy Efficient AODV (CLEE-AODV). Using this CLD approach, they implemented the required changes in the route discovery process in the AODV. Through simulation results, they showed that the CLEE-AODV routing protocol has better performance enhancements than AODV, in terms of total transmission power, energy consumption per node, energy efficiency, and throughput. [PERSON] and [PERSON] [202] proposed an energy-efficient cross-layer routing protocol for heterogeneous cluster-based WSNs. The protocol is named ATEER to justify that it is Adaptive Energy-Efficient and based on the Threshold concept.