## 4 Proposed Work of MANET-ESO in IoT  
The MANET is using the proposed MANET-ESO in an IoT environment, and it increases the rate of trust and successive communication between sensor nodes. The IoT is consisting of WSN techniques with internet service. The mutual internet world of the electronics domain is growing with intelligent network applications. The IoT sensors are successively gathering physical incidents to digital data in different time intervals. Nevertheless, IoT data transmission delay and power utilization are increased due to the uncertainty of sensor nodes. However, the proposed model increases throughput and minimizes energy factors. This MANET Algorithm has improved network performance through trust and the best route optimization method. In Figure 1, different sensor nodes are connected to the adjacent mobile nodes. Additionally, mobile nodes are forming the cluster using a high density of sensors in that network.  
Figure 1: Heterogeneous Network Constructed by Sensor, MANET and Cloud storage through the Internet.  
The CH controls, monitors and collects data from sensors. The CH is dynamically changing in the network in terms of the distance from the sensor to the mobile node and the energy level of the mobile node. In the MANET, the information is linked to the gateway node through the CH node, adjacent nodes and gateway nodes using the internet cloud network. The route created in MANET optimizes the energy and enables trusted route paths. Table 1 shows the abbreviations used in the manuscript.  
In this case, available routes and the best routes are created sequentially using the proposed model. In addition, the MANET transmits and stores data or receives commands using the Internet service. Consequently, a heterogeneous network is created to transfer or receive the data through the internet between MANET and the cloud systems (via gateways). The gateway nodes have created the link between the MANET and the cloud routing algorithm.  
In this case, the overall performance of the network is higher than a simple IoT network with optimal performance metrics (throughput, energy, delay, packet delivery ratio and routing overhead) while using MANET-ESO (Algorithm 1).  
```
Initialized: Simulation area considered with n--number of sensor nodes  CH--Cluster Head  m--number of mobile nodes  GW--Gate Way nodes  ECH--residual energy of CH  r = number of discovered routes  E\({}_{T}\) = Total residual energy of the node  E\({}_{th}\) = Energy Threshold Level  E\({}_{min}\) = Route total Energy threshold level  D\({}_{ij}\) = distance between sensor nodes  H\({}_{p}\) = destination sequential count  If m is connected with more than one number of n, //cluster head selection  Then, m = CH  else, m- act as an adjacent node in the network
```  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Abbreviations** & **Details** \\ \hline MANET-ESO & Mobile Adhoc Network-Energy Saving Optimization  IoT & Internet of Things \\ WSN & Wireless Sensor Network \\ IP & Internet Protocol \\ DNS & Domain Name services \\ DoS & Denial of Service Attack \\ CH & Cluster Head \\  E\({}_{Ri}\) & Residual Energy of the node \\  E\({}_{p}\) & Energy required to transmit one packet \\  P\({}_{n}\) & Total number of packets \\  T\({}_{Total}\) & Total Time \\ T\({}_{Active}\) & Active node Time \\ T\({}_{Sleep}\) & Sleepy node Time \\ T\({}_{Idle}\) & Idle node Time \\ D\({}_{ij}\) & Distance between adjacent node i to j \\ E\({}_{CH}\) & CH residual energy \\ E\({}_{MANET}\) & MANET discovered route residual energy \\ R\({}_{t}\) & Trusted Route \\ \hline \hline \end{tabular}
\end{table}
Table 1: Abbreviations and Details.