# BDS: An Efficient Spark-Based Big Data Processing Scheme for Cloud Fog-IoT Orchestration
## 4 System Model and Methodology
### Components of the Fog-IoT Hierarchical Overlay Network and BDPS Architecture
\begin{table}
\begin{tabular}{l l} \hline \hline
**Performance Criterion** & **Baselines** \\ \hline Throughput [Mb/s] & Cloud Orchestrated Fog-IoT network \\ Node Failure Rate [\%] & Spark-RDD based Fog-IoT Controller Scheduling \\ \hline Computational Delay [s] & Schedule-Aware Bundle Routing (SABR) \\ \hline \multicolumn{3}{c}{Preemptive Scheduling Regressor} \\ Bandwidth Prediction [Kb/s] & Spark-RDD Regressor \\ \multicolumn{3}{c}{Asymptotic Regressor} \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Performance criteria and baselines. \begin{table}
\begin{tabular}{l l} \hline \hline
**Simulation Parameters** & **Values** \\ \hline \multicolumn{3}{c}{_Software Centric Parameters_} \\ \hline Network emulator & OMNET++ 5.5.3; Jupyter Notebook 6.1.0; \\  & ns-3.2.1; iFogSim \\ Cloud storage platform & Owncloud 10.3 \\ Packet analyzer & Wireshark Packet Analyzer \\ Programming language & Python 3.5.3, Java 9, C++17 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Parameters of the simulation environment (software centric). BDPS shows higher throughputs of 10 ms in fog, 8 ms in IoT and 7 ms in cloud, respectively, and the data offload remains 1.4% in 1000 packet deliveries. This data execution pattern of BDPS shows consistency within the three-tier data distribution architecture across intended nodes. Less data offload resembles better data deliveries across the fog-IoT network continuum. The FW, DA and AH algorithms perform the same in terms of data offload around the cloud, fog, and IoT orchestration, and employ lower data throughput. Comparing to BF and others, the BDPS performs better, delivering the map reduction data delivery pattern toward the network edges. Network Overhead Generation Scenario over the FW, AH, BF, DA and BDPS Algorithms in Cloud, Fog, and IoT Orchestration

Figure 6 describes that the Bellman-Ford (BF) algorithm has a higher network overhead in the fog continuum rather than cloud and IoT. BF does not employ data mapping toward intended users. The data offloads are higher in the fog, and cloud (rather than IoT) redirects the stack overload of data processing within the three-tier mesh architecture. Hence, BF, DA, FW and AH are not a worthy choice for the increased network overhead over system run time. BF declares a higher network overhead of 12 ms in fog, showing a multiplication of the data packet offload of 1.6% in 1000 packet deliveries. However, having a resilient map reduction data architecture, the BDPS shows lower network overhead of 7 ms in fog, 6.5 ms in cloud and 5.9 ms in IoT, respectively, and the data offload remains 0.7% in 1000 packet deliveries. This data execution pattern of BDPS shows gradual consistency within the three-tier data distribution architecture across intended nodes. Less network overhead resembles better data deliveries across the fog-IoT network continuum. The FW, DA and AH algorithms show a gradual increase in the data offload similar to BF throughout the cloud, fog, and IoT orchestration, and employ higher data offload. Comparing to BF and others, in terms of network overhead, BDPS performs better, delivering the map reduction data delivery pattern toward the network edges. Figure 5: Throughput of data execution among existing algorithms and BDPS over fog-IoT mesh architecture. Packet Drop Generation Scenario over the FW, AH, BF, DA and BDPS Algorithms in Cloud, Fog, and IoT Orchestration

Figure 7 shows that the Bellman-Ford (BF) algorithm has a higher packet drop in the cloud continuum rather than IoT and fog. The BF does not employ data mapping toward intended users. The data hand-offs or packet drop are higher in the cloud, and IoT (rather than fog) redirects data stack overloads within the three-tier mesh architecture. Hence, BF, DA, FW and AH are not a worthy choice for increased packet drops over the system run time. BF declares a higher packet drop of 12 ms in fog, showing a multiplication of the packet offload of 2.2% in 1000 packet deliveries.