Due to extensive pipeline dissemination in the oil and gas refinery, the nodes need to be placed in a grid formation. As such, since most oil and gas industry applications require continuous data gathering, a heavy data stream will be introduced in the network traffic, mainly when the network density is high. As a result, performance degradation and poor energy consumption will occur. Ad hoc on-demand distance vector and optimized link state routing protocol have been simulated to investigate these issues further. Due to packet congestion, the network experiences a domino effect on the performance, such as packet loss, throughput degradation, and poor energy consumption. Thus, a tailored solution is required since oil and gas industry relies heavily on sensor data to keep track of pipelines condition to prevent anomalous events from happening. The proposed algorithm has been developed to optimize the network performance by dividing the traffic into two and by reducing the flooding during route discovery. The results have shown better network performance and energy consumption can be achieved using the proposed algorithm when compared to the others.
Multiphase Flow Effects in a Horizontal Oil and Gas Separator