# Game-Theory-Based Multimode Routing Protocol for Internet of Things
## 2 Related Work  
In ad hoc networks, GT can be used for a variety of purposes. GT has been used to create routing protocols for several types of ad hoc networks [10]. The major goal is to meet the QoS requirements. A ZRP-like GT-based protocol has been proposed by [PERSON] et al. [11]. In this mechanism, the node extinction rate is calculated to manage the network architecture. Moreover, to improve ad hoc QoS routing, a routing protocol based on the energy efficiency of zones is devised. This research describes a new way of enhancing the energy economy of ZRP-based protocols that control network topology by guessing node life expectancy. Furthermore, to increase QoS parameters, a game is paired with an efficient ZRP-based protocol. The authors state that the main objectives are to a) manage network topology according to the energy consumption rate; and b) improve QoS-aware techniques in terms of bandwidth, PDR, and some other parameters. [PERSON] and [PERSON] [9] presented a technique that solely focuses HANETs. It focuses on cluster-based heterogeneous networks and comprises six phases. The GT model that is employed is a non-cooperative one. The basic goal is to construct clusters in a HANET as quickly as possible. The mixed strategies of several heterogeneous nodes are optimized using linear programming and GT. A transmission power control-based strategy is described in the paper [12], which allows mobile nodes to balance transmission rate and power consumption to achieve a trade-off between transmission rate and power consumption. For each node, two tables define and update the average transmission rate as well as the amount of time the neighboring node is used for data transfer. Some GT-based routing methods in ad hoc networks are primarily concerned with security. For device-to-device networks, [PERSON] et al. [13] have suggested a secure GT-based routing algorithm. This proposed method operates in cluster-based networks. All data traffic is redirected through some secure routes that have been defined. GT has been used by the authors to develop simple routing and load-balancing protocols. There is no mechanism in these strategies to handle diverse nodes in a wider network. The majority of GT-based routing methods place a premium on selfish node management. [PERSON] [14] proposes a reliable GT-based routing technique for a wireless sensor network (WSN) with certain selfish nodes. To balance resource consumption and reliability, a game model is applied. For resource-constrained network nodes, the network's global information is not necessary. Furthermore, all nodes are free to act selfishly under this technique. Each player node's four primary elements are taken into account in this proposed effort. This study takes into account transmission power, connectivity, dependability, and collision. Furthermore, network node heterogeneity is supported by the findings. In recent years, a number of studies have been published proposing hybrid routing methods. The main focus of the majority of research projects has been on improving QoS parameters. The major goal is to improve targeted ad hoc networks by taking into account the following factors: latency, node energy, PDR, routing and processing overhead, and throughput [15]. ZRP [16] is a basic hybrid routing protocol that has been developed for many sorts of ad hoc networks. Various upgraded or modified variants of ZRP have been proposed in recent literature. The \"Dynamic Relationship-Zone Routing Protocol\" (DRZRP) [17] is a ZRP-based protocol that focuses on relational zones rather than normal ZRP zones. The mechanism states that it is obvious for some nodes to communicate with non-zonal nodes on a regular basis. The zones, with a specified radius, are created based on the frequency of data transmission among the nodes. These zones are dynamically maintained, and the DRZRP algorithm decides proactive routing behavior inside these zones. This work is mainly concentrated on the delays and communication and processing overhead.