Adaptive congestion control in cognitive industrial wireless sensor networks

Strict quality of service requirements of industrial applications, challenged by harsh environments and huge interference especially in multi-vendor sites, demand incorporation of cognition in industrial wireless sensor networks (IWSNs). In this paper, a distributed protocol of light complexity for congestion regulation in cognitive IWSNs is proposed to improve the channel utilization while ensuring predetermined performance for specific devices, called primary devices. By sensing the congestion level of a channel with local measurements, a novel congestion control protocol is proposed by which every device decides whether it should continue operating on the channel, or vacate it in case of saturation. Such a protocol dynamically changes the congestion level based on variations of non-stationary wireless environment as well as traffic demands of the devices. The proposed protocol is implemented on STM32W108 chips that offer IEEE 802.15.4 standard communications. Experimental results confirm substantial performance enhancement compared to the original standard, while imposing almost no signaling/computational overhead. In particular, channel utilization is increased by 56% with fairness and delay guarantees. The presented results provide useful insights on low-complexity adaptive congestion control mechanism in IWSNs.