Congestion control is necessary for enhancing the quality of service in wireless sensor networks (WSNs). With advances in sensing technology, a substantial amount of data traversing a WSN can easily cause congestion, especially given limited resources. As a consequence, network throughput decreases due to significant packet loss and increased delays. Moreover, congestion not only adversely affects the data traffic and transmission success rate but also excessively dissipates energy, which in turn reduces the sensor node and, hence, network lifespans. A typical congestion control strategy was designed to address congestion due to transient events. However, on many occasions, congestion was caused by repeated anomalies and, as a consequence, persisted for an extended period. This paper thus proposes a congestion control strategy that can eliminate both types of congestion. The study adopted a fuzzy logic algorithm for resolving congestion in three key areas: optimal path selection, traffic rate adjustment that incorporates a momentum indicator, and an optimal timeout setting for a circuit breaker to limit persistent congestion. With fuzzy logic, decisions can be made efficiently based on probabilistic weights derived from fitness functions of congestion-relevant parameters. The simulation and experimental results reported herein demonstrate that the proposed strategy outperforms state-of-the-art strategies in terms of the traffic rate, transmission delay, queue utilization, and energy efficiency.
https://link.springer.com/article/10.1007/s11276-020-02289-0
