# Performance Evaluation of Mobile RPL-Based IoT Networks under Hello Flood Attack
## 5 Methodology and Setups  
### Simulation Setups  
Using the data in Table 1, a set of simulations were run in a 100 m \(\times\) 100 m space to fully investigate RPL's performance in a range of different mobility scenarios. The network configuration included varying numbers of sensor nodes ranging from 10 to 60, all governed by a singular gateway node. The simulation employed Z1 motes and utilized the UDP transport layer protocol, along with the IEEE 802.15.4 PHY and MAC layers. The Zolertia One (Z1) IoT platform, developed by Zolertia R, utilizes the energy-efficient Texas Instruments MSP430 Micro-Controller (MCU) as its Central Processing Unit (CPU), along with the Chipcon CC2420 radio module for wireless communication [16]. Mobility was a crucial consideration in our experiments, facilitated by integrating a dedicated mobility plugin into the Cooja simulator. This expansion allowed us to effectively simulate mobile IoT applications. Movement patterns among mobile nodes were generated using BonnMotion, an open-source Java-based software developed at the University of Bonn in Germany [17]. The configuration parameters related to the movement of the nodes, including their velocity, pause times, and acceleration, are based on the values specified in the original mobility models as published in the corresponding research papers [7].  
For neighbor discovery and maintenance, \"HELLO\" packets, specifically DIO messages, were used. These \"HELLO\" packets typically ranged from 20 to 60 bytes in size. The packet size is designed to be small to minimize overhead and conserve bandwidth and energy, which are critical in Low-Power and Lossy Networks. The transmission interval of these \"HELLO\" packets was dynamically managed by the Trickle timer algorithm, which adjusts the interval based on network stability. The minimum interval (I\({}_{\text{min}}\)) was set to a few seconds, with the interval doubling each time up to a maximum period if no inconsistencies were detected, balancing rapid dissemination of routing information and minimizing unnecessary traffic.  
Communication was facilitated through a radio medium modeled as a unit disk graph, with a transmission range established at 50 m. To assess network robustness, the experiment introduced dynamic elements by designating 10%, 20%, 30%, and 40% of the nodes as attackers. Furthermore, 60% of the nodes were set as mobile, moving at a consistent speed of 1 to 2 m/s. Data packets, each sized at 30 bytes, were transmitted at intervals of 60 s,  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Settings** & **Values** \\ \hline Transmission range & 50 m \\ Dimension area & 100 m \(\times\) 100 m \\ Sensor nodes’ number & 10, 20, 30, 40, 50, 60 \\ Attacker nodes’ number & 10\%, 20\%, 30\%, 40\% \\ Radio medium & Unit disk graph medium \\ Transport layer protocol & UDP \\ PHY and MAC layer & IEEE 802.15.4 \\ Data packet sending interval & 1 to 2 m/s \\ Mobility models & CMM, RPGM, NCM, PMM \\ \hline \hline \end{tabular}
\end{table}
Table 1: Simulation settings.  
enabling a comprehensive analysis of the network's performance and resilience under the specified conditions. This approach ensures efficient network operation, maintaining connectivity while conserving energy. The simulations extended for one hour, allowing for an accurate observation of the network's actual performance.