A Reliable Adaptive Rate Congestion Control for Landslide Monitoring in Wireless Sensor Network

Abstract

The emergence of Wireless Sensor Network (WSN) has developed significant potentials for real-time and remote monitoring systems, such as landslide monitoring, military surveillance as well as healthcare and home automation. Due to stringent requirements of real-time data transmission, most of these applications deserve high Quality-of-Services (QoS) assurance. However, sudden burst of traffic is likely to occur during WSN event detection, leads to buffer-overloaded problem, which is known as congestion. Obvious consequences include high packet loss that will severely degrade overall network performance. Such issues provide the motivation for this research, leading to the introduction of an Adaptive Rate Congestion Control (ARCC) mechanism, which is based on the integration of Selective Forwarding Node (SFN) and Relaxation Theory (RT). This integration technique has achieved huge reduction in packet loss rates (0.014%) as well as minimized the end-to-end delay that is proven to be within an allowable realtime threshold of 150 ms.