# Survey on Power-Aware Optimization Solutions for MANETs
## 5 Challenges and Future Research Directions
### Future Directions  
* Modeling Optimizations: In MANETs, flooding strategies such as Multi-Point Relays (MPRs) flooding can enhance the efficiency of routing protocols for MANETs in terms of energy and time consumption through the use of an energy-aware mechanism. Indeed, an energy-aware mechanism is required to control the flooding process in MANETs when route discovery is performed. Such an energy-aware mechanism (called Energy Aware Flooding) was proposed in [233]. It is noteworthy that this mechanism also improves the security of routing schemes to avoid Denial-of-Service (DOS) flooding attacks in MANETs. Creating and testing new mathematical models for flooding techniques, those mainly working under well-established power-efficient routing schemes will be very challenging and promising [234]. This direction will help researchers to propose new energy-aware flooding mechanisms in MANETs. * Hybrid optimization algorithms for topology management in cluster-based MANETs. In cluster-based MANETs, new optimization algorithms are required for making effective clustering and adjusting power and energy parameters using topology management. The management of the network topology demands the construction of a graph that is equivalent to the real network. After that, the optimization algorithm will perform the clustering of this graph to make an optimal CH. To adjust power, the optimization algorithm can be based on an objective function that considers some factors that involve power, connectivity, mobility, link lifetime, and distance. An example of such an optimization algorithm is the Chronological-Earth Worm optimization Algorithm (C-EWA) [11] that does effective clustering and adjusts power and energy parameters using topology management. In MANETs, the regular re-clustering of nodes is required, but this process generates a network overhead (overload). To reduce this overload, [PERSON] and [PERSON] [235] presented a clustering method that optimizes energy consumption in routing. The authors proposed a method called Imperialist Competitive Algorithm (ICA) that is based on evolutionary algorithms. ICA via numerical coding can find proper CHs. By estimating the mobility direction of nodes, it prevents the additional re-clustering of nodes. As a result, it reduces the overload generated from the re-clustering process. In ICA, a fitness function is used that accepts various parameters (e.g., battery power, network range, node degree, node velocity, and coverage rate of nodes) as inputs to increase the efficiency of routing. The authors validated the accuracy and reliability of their method using statistical tests and three sample case studies, including different numbers of nodes and ranges. * Energy-efficient routing based on Learning Automata (LA): The LA theory can be used for improving the performance of energy-efficient routing protocols for MANETs. A learning automaton is a machine learning algorithm that selects its current action based on past experiences from the environment. Recently, based on the LA theory, [PERSON] et al. [236] suggested a stable and energy-efficient routing algorithm for MANETs. First, they constructed a novel node stability measurement model and defined a successful energy ratio function. On that starting point, they gave the node a weighted value, used as the iteration parameter for LA. After that, the authors developed an LA theory-based feedback mechanism for the MANET environment to optimize the selection of available routes and to verify the convergence of their algorithm. The experiments showed that the suggested LA-based routing algorithm obtained the best performance in route survival time, energy balance, energy consumption, and satisfactory performance in end-to-end delay and PDR. * Energy-Efficient Routing Mechanisms for Cloud-Assisted MANETs: In 5G networks, the Device-to-Device (D2D) communication has increased the rate of data transmission among mobile nodes. A Cloud-Assisted MANET enhances the features of a MANET by joining it with cloud data centers and D2D communication.