Finding an appropriate radio propagation model for rate aware congestion control mechanism in wireless sensor networks

Congestion control techniques are considered to be one of the most imperative ways to overcome various challenges in wireless sensor networks (WSNs). Undeniably, congestion has a substantial impact on Quality of Services (QoS) parameters including: packet delivery ratio (PDR), throughput and delay. Another reason for poor QoS is decreased signal strength which could be due to reasons like: larger distance, reflection, refraction, and scattering. Therefore, in this paper, the issue of congestion and path loss are resolved using two-step approach. In the first step, a novel rate aware congestion control mechanism is proposed which improves the PDR and throughput by minimizing network delay. The proposed approach communicates using constant bit rate through user datagram protocol to overcome congestion in a more efficient way. Besides this, the proposed mechanism adapts a queue management algorithm that helps in identifying the level of congestion which are further categorized into various levels (Level-1, Level-2 and Level-3) based on the received congestion information. In the second step, RACC is implemented over various propagation models namely: Free space, Shadowing and Two-Ray to find most appropriate model for WSNs. Finally, the validation of the optimum radio propagation model is checked by comparing these models on the basis of parameters: like End-to-End delay, PDR, throughput, MAC overhead, normalized overhead, average remaining energy and packet loss percentage using NS2 (Network Simulator 2) simulator. The results show that for RACC model, two-ray ground experiences least packet loss percentage (5%) in comparison to shadowing and free space radio propagation model. However, it touches 47% when the number of connections is increased to 26, which is still better than the shadowing radio propagation.