Congestion Control in Wireless Sensor Networks based on the Lotka Volterra Competition Model

Next generation communication networks are moving towards autonomous wireless infrastructures, as for example, Wireless Sensor Networks (WSNs), that are capable of working unattended under dynamically changing conditions. Over the last few years, WSNs are being developed towards a large number of multimedia streaming applications, e.g., video surveillance, traffic control systems, health monitoring, and industrial process control. However, WSNs face important limitations in terms of energy, memory and computational power. The uncontrolled use of limited resources in conjunction with the unpredictable nature of WSNs in terms of traffic load injection, wireless link capacity fluctuations and topology modifications (e.g. due to node failures) may lead to congestion. Congestion can cause deterioration of the offered quality of service (QoS). This study proposes a bio-inspired congestion control approach for WSNs streaming applications that necessitate controlled performance with graceful degradation. The proposed approach prevents congestion in WSNs by regulating the rate of each traffic flow based on the Lotka-Volterra population model. Performance evaluations reveal that the proposed approach achieves adaptability to changing traffic loads, scalability and fairness among flows, while providing graceful performance degradation as the offered load increases.