Recently, the fundamental problem with Hybrid Mobile Ad-hoc Networks (H-MANETs) is to find a suitable and secure way of balancing the load through Internet gateways. Moreover, the selection of the gateway and overload of the network results in packet loss and Delay (DL). For optimal performance, it is important to load balance between different gateways. As a result, a stable load balancing procedure is implemented, which selects gateways based on Fuzzy Logic (FL) and increases the efficiency of the network. In this case, since gateways are selected based on the number of nodes, the Energy Consumption (EC) was high. This paper presents a novel Node Quality-based Clustering Algorithm (NQCA) based on Fuzzy-Genetic for Cluster Head and Gateway Selection (FGCHGS). This algorithm combines NQCA with the Improved Weighted Clustering Algorithm (IWCA). The NQCA algorithm divides the network into clusters based upon node priority, transmission range, and neighbour fidelity. In addition, the simulation results tend to evaluate the performance effectiveness of the FFFCHGS algorithm in terms of EC, packet loss rate (PLR), etc.

Mobile ad-hoc network (MANET) is a category of ad-hoc network that can be reconfigurable its network. MANETS are self-organized networks, that can use the wireless links to connect various networks via mobile nodes: but it consumes more energy and it also has routing problems. This is the major drawback of being connected with the MANET technology. Therefore, this study proposes a new protocol as deep Q-learning network optimized with chaotic bat swarm optimization algorithm (CBS)-based optimized link state routing (OLSR) (CBS-OLSR) for MANET. This protocol reduces MANET energy usage and adopts OLSR multi-point relay (MPR) technology. MANET's OLSR and the CBS algorithm utilize a similar method to locate the best optimum path from source to destination node. By embedding the new improved deep Qlearning and OLSR algorithms, both are used for optimizing the MPR sets selection, it can efficiently diminish the energy consumption in the network topology, but automatically increase the lifespan of the network. It also enhances the package delivery ratio and decreases end-to-end delay. The experimental outcomes prove that the proposed protocol is reliable and proficient that is appropriate for numerous MANET applications. K E Y W O R D Schaotic bat swarm optimization, deep Q-learning algorithm, end-to-end delay, mobile adhoc network, MPR (multi-point relay), optimized link state routing, packet delivery rate | INTRODUCTIONMANET is an autonomous system that consists of individually connected set of self-configuring nodes that is implemented using a number of techniques, viz Bluetooth or WLAN. 1 The feature of MANET is autonomous, due to every node treating its host and router simultaneously. 2 To communicate among the distant nodes, they depend on direct communication with multi-hops. These advantages allow them to accommodate multiple nodes and decentralize management with its structure at any time. 3 Unlike other wireless systems, MANET has lack of central authority to monitor traffic transmission. 4 MANET systems have an infrastructure with a lesser configuration of corresponding nodes that are connected by wireless connections. The nodes are moving spontaneously or rather in a random section. 5 From node to network level, security in MANETs is important. 6 Owing to the dynamic nature of MANETs, there needs to be an acceptable level of trust. 7,8 Due to the dynamic nature and characteristics of MANETs, security on the MANET is more challenge

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