# Game-Theory-Based Multimode Routing Protocol for Internet of Things
## 1 Introduction  
Various routing protocols for IoT have been proposed in the literature. Reactive, proactive, and hybrid methods are the most common [1]. In proactive routing, each node maintains an up-to-date routing table. To detect variations in the network, the nodes broadcast some control messages in the network. The reactive protocols are on demand: the source nodes generate some routing message whenever they need to send some data. Routing messages are flooded throughout the entire network. This mechanism is known as route discovery. When a path is determined, bandwidth is employed to communicate information [2]. Both protocols have advantages and disadvantages. The type of network, features, and capabilities of nodes have a noteworthy effect on the efficiency or performance of various protocols. For example, nodes with higher mobility ratios outperform others when using the dynamic source routing (DSR) protocol [3]. According to this fact, we can assume that highly mobile nodes favor pure reactive protocols. Similarly, proactive protocols improve their packet delivery ratio (PDR) as the network size increases [4]. Additionally, proactive routing strategies result in fewer end-to-end delays. A hybrid of reactive and proactive protocols has been proposed by many researchers. Zone routing protocol (ZRP) [5] is the simplest basic hybrid protocol. The proactive routing is limited to the node's immediate proximity in this routing protocol. The major goal is to reduce total network costs while taking into account the advantages and disadvantages of both types of reactive and proactive protocols. Hybrid routing technologies combine reactive and proactive routing capabilities. The network is split into several sections in such protocols. The most typical option is to divide the network into zones or clusters [6]. If we partition a network into heterogeneous clusters or zones, there will be no use for the heterogeneity of member nodes within these segments. If we do not bind the nodes to a certain location, the heterogeneous routing protocols can be more efficient. Furthermore, the formation and frequent update of clusters, as well as the nomination of cluster heads (CHs), may result in additional node overhead [7]. Both clustered and non-clustered networks should be covered by the technique. Multiple routing protocols can be used in the same network. In other words, by utilizing some gateway nodes, many different ad hoc networks can be merged into a single heterogeneous ad hoc network (HANETs). The basic goal of a larger network is to share and optimize resources [8]. Different nodes can use the help of other network nodes to get shorter pathways and transfer data to inaccessible nodes. The resourceful CHs are commonly regarded to be the gateway nodes [9]. Any programmable node should be assigned to the role of the gateway node. Furthermore, the role of gateway nodes in a heterogeneous network should not be confined to connecting distinct nodes. There should be a framework in place that allows gateway nodes to choose their own routing behavior. When choosing their routing behavior, nodes should take into account both their own parameters and the capabilities of the network. A node with proactive neighborhood, for instance, should adopt proactive routing. Similarly, in order to use less energy, nodes with lower remaining energies should switch to reactive routing. While communicating with other gateways and ordinary network nodes, gateway nodes should be able to intelligently choose a routing behavior. Game theory (GT) is an economics and mathematics branch, but can be applied to any discipline to help people choose between several solutions. In the realm of networking, the GT technique is employed for a variety of objectives. Routing creation, application focus, network security, and network administration are the four fundamental factors that are used to model the relationship between wireless networks and GT [10].