# Bat Optimized Link State Routing Protocol for Energy-Aware Mobile Ad-Hoc Networks
## Literature Review  
Mobile devices consume energy and rely on networks without infrastructures, such as the MANET, or networks with infrastructure. Different protocol problems are associated with MANETs, specifically, the procedure of discovering optimal paths between the source and the destination nodes, which involves high Energy Consumption (EC) from broad node communications [25]. When the source node sends data to the destination node, the appropriate path to their destination must first be identified by broadcasting routing requests. This activity consumes more power than data transmission, and the risk of connection failure is increased by the flexible processes of mobility-enhanced nodes. When the connection fails, routing requests must be re-initiated by the source nodes; this phenomenon increases the EC related to node operations [26]. The different routing protocols available in MANETs are classified as reactive, proactive, and hybrid [18]. The AODV is a typical example of a reactive protocol. In this protocol, routes are formed only when the source needs to transmit data to a destination [15]. An example of a proactive protocol is table-driven protocol, in which the updated information is maintained between the routes from every node to all other nodes present in the network [16]. Finally, the hybrid routing protocol attempts to integrate elements of the proactive and reactive routing protocols [18]. The central idea of hybrid routing is that proactive connections are available in areas with low mobility, whereas reactive connections are available in areas with high mobility [19]. Network routing problems have been recently solved through the implementation of different intelligent algorithms, such as African Buffalo Optimization (ABO) [6], ant colony optimization (ACO) [27], Genetic Algorithm (GA) [7; 28], Artificial Bee Colony (ABC) [29], and Practical Swarm Optimization (PSO) algorithm [30].  
[PERSON] et al. [6] introduce a new routing scheme cellular automata African Buffalo Optimization (CAABO) based on Cellular Automata (CA) and African Buffalo Optimization (ABO) algorithms. The CAABO attempts to discover the paths that fulfil the delay requirements and limitations as well as improving the energy usage of the network. [PERSON] et al. [31] propose a new energy-efficient routing protocol by using different Quality of Service (QoS) parameters such as hops count, End-To-End (E2E) delay, and bandwidth. These parameters are managed via the GA algorithm to get an optimal solution. The new protocol is called Energy-Based OLSR (EBOLSR). [PERSON] et al. proposed a new energy-aware method called the ACO-EEOLSR that contains the ACO-enhanced approach to obtain an energy-efficient OLSR for the MANET technology [32]. Alternatively, a clustering algorithm to be used in the OLSR protocol for a new energy-aware method is proposed by [33]. This new method is aimed to decrease the E2E delay while increasing the lifespan of the network. A study by [PERSON] et al. [34] proposed an invasive weed PSO, a hybrid algorithm that is combined with the OLSR protocol to reduce the E2E delay while improving the throughput of the network. A new hybrid algorithm called PSO sigmoid increasing inertia weight is proposed for the selection of Multipoint Relay (MPR) to improve the performance of OLSR [35]. In addition, a new OLSR protocol mechanism that uses the willing concept to improve EC and increase the lifespan of the network is also suggested [36].