## 2 Related Work  
Using a small number of mobile nodes to assure connectivity while maintaining overall coverage while working within resource constraints is a difficult task. A critical topic that has been examined in recent years in the literature is that in the event of battery drain, harsh weather or any other fault with a node, the system will fail. This field has seen a slew of new algorithms come to light. The system will fail if the battery runs out, the weather is bad, or a node fails. Many new algorithms have been developed in this area. Sensor nodes are spread at random using an aerial approach in most cases [5]. This type of deployment may result in a non-uniform distribution of mobile nodes over the AOI, with higher densities in certain areas and lower densities in others. As a result, in this scenario, relocation is required to assure connectivity between mobile nodes and end users while also increasing coverage area. The literature has addressed the issue of connectedness, and numerous solutions have been presented [6; 7; 8]. To solve the connectivity problem, coverage gaps in certain places, must be avoided. As a result, it's crucial to strike a balance between connectivity and connectedness. Several methods have been tested in recent years. The concept of a two-connected network was proposed by the authors of [8]. According to this technique, each set of nodes in the network must have at least two linked pathways. This approach uses a two-degree connection and requires each node to hold two hopes. A cascading movement of nodes is recommended in [9] as a technique to restore connection when a node fails. This strategy calls for the failing node to be replaced by a neighboring node. At a redundant node, the cascade relocation mechanism begins and ends. For the analysis of mobile ad hoc networks, a technique is proposed that suggests using a probabilistic, energy-conscious broadcast calculus. In order to make the deterministic decision between the probability distributions across target states, the semantics of our model are represented in terms of [PERSON]'s probabilistic automata that are driven by schedulers [10]. With the help of a formal specification in AWN (Algebra for Wireless Networks), a process algebra that has been especially designed for the modelling of Mobile Ad Hoc Networks and Wireless Mesh Network protocols, here a thorough analysis of the Ad hoc On-Demand Distance Vector (AODV) routing protocol is presented. The explanation of how the logic and proofs may be quite simply modified to protocol variants is one of the paper's significant contributions [11]. Mobile ad hoc and sensor networks are crucial in a number of application areas. The use of wireless links and the mobility of the nodes makes networks vulnerable to security attacks; among them, jamming attacks are sneaky and involve one or more nodes sending out false packets repeatedly to keep some wireless links busy. With regard to the Hybrid Wireless Mesh Protocol (HWMP), it assesses a network's susceptibility to jamming and unintentional interception using two different routing algorithms. C3R [12] proposes a method for restoring coverage-aware connections in mobile sensor networks by replacing failed nodes with adjacent nodes, moving back and forth between the failed node's location and their initial position. The node that arrives first at the failed node creates the timeline for changing the turns of these nodes. A similar approach, known as RIM, is described in [13]. (Recovery by invert motion). In RIM, the failing node was recovered by its neighbouring nodes via inversion migration to the failed node's location. The basicidea is to make use of the surroundings. If the HEART BEAT message is not received, they will be the first to know of a node failure. As a result of their inward match towards the malfunctioning node, the network link is restored. In DARA [14], an approach for detecting cut vertices was devised by selecting a suitable neighbour node for relocation.