# Game-Theory-Based Multimode Routing Protocol for Internet of Things
## 3 Proposed Mechanism  
The proposed study's major goal is to design and create a network that uses many routing protocols to function together. In a single network, heterogeneity is measured in terms of distinct routing protocols. There may be nodes in a heterogeneous network with varying capabilities and parameters. Energy level, energy consumption ratio, mobility ratio, PDR, and so on are examples of these parameters. The nodes are meant to utilize a specific routing protocol based on the type of parameters.  
Some intelligent nodes, known as smart nodes, are programmed to comprehend the routing behavior of various underlying heterogeneous nodes. By acting as gateways  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline
**Paper** & **Network and Focus** & **Summary** & \\ \hline [PERSON] et al. (2020) & Homogeneous Clustering &  
between the heterogeneous nodes, these nodes make it easier for them to communicate with one another. Furthermore, when these smart nodes communicate with one another, the most appropriate default routing behavior for them can be established to enhance the overall network's performance. A game-theory based on the prisoner's dilemma is used to change default routing behavior. This is an evolutionary process in which nodes evaluate the required parameters over time and adjust their routing behavior accordingly.  
Two basic routing protocols are chosen to be employed to connect the nodes in the underlying ad hoc network. These protocols can be of any type. We generalize this by taking the two categories of reactive and proactive protocols. For communication, all the smart nodes can utilize one or both protocols. The preprogrammed nodes operate on a particular routing protocol and cannot be adapted. The smart nodes can include both routing characteristics. Figure 1 depicts the three different classes of nodes. The nodes are classified based on their behavior. A HANET can be created by joining two or more networks that each have proactive and reactive nodes.  
With the help of Figure 1, the routing capacity of smart nodes can be explained. In this diagram, a smart node communicates proactively with a proactive node while also being perceived as a member of its own family by a reactive node. Depending on their preferences and the GT, smart nodes adjust their routing behavior towards other smart nodes. A smart node can also operate as a connector between two separate nodes.  
Figure 2 depicts a small network with heterogeneous nodes using three different routing strategies: proactive, reactive, and smart routing. There are five proactive and eight reactive nodes. This network could alternatively be thought of as a hybrid of two networks combined with the help of some smart nodes. Nodes with similar routing protocols may usually communicate with one another. The proposed smart routing technique, on the other hand, allows nodes with various routing protocols to communicate more effectively. The image depicts two sample scenarios, which are further detailed in Table 2:  
Figure 1: Proposed types of nodes and the in-between communication modes.  
We have two noteworthy cases, as shown in Figure 2 and Table 2. Both the source and destination nodes (R31 and R36) in the first scenario use a reactive routing protocol. A shorter route can be established by involving nodes from different classes when employing the proposed smart nodes. In case 2, two reactive nodes (R52 and R42) cannot connect to each other. These reactive nodes can be linked by enlisting the help of a proactive node and the proposed smart nodes.  
This section is further broken into the following subsections: in Section 3.1, several sample network scenarios are given. Section 3.2 discusses the network's key assumptions and characteristics. The game model is explained in Section 3.3, and the structure and actions of smart nodes are explained in Section 3.4.