Performance analysis of an adaptive rate congestion control in wireless sensor networks (WSN)

Abstract

The emergence of Wireless Sensor Network (WSN) field has developed beneficial potential for real-time and remote monitoring system such as landslide monitoring, military surveillance as well as home automation and healthcare monitoring system. Most of these applications emphasize the need to preserve high Quality-of-Services (QoS). A wireless sensor network consists of remotely deployed wireless sensor nodes in a physical phenomenon. The main task of sensor nodes is to collect specific data from surrounding environment and then route it to the base station or sink. When a particular event is detected, the sensor nodes become activated and there is a sudden burst of traffic towards the sink. This may lead to buffer-overloaded problem which is known as congestion, which cause packet drops that finally degrades overall network performance. Such issues provide the motivation for this dissertation, which lead to the introduction of an Adaptive Rate Congestion Control (ARCC) mechanism. The integration of Selective Forwarding Node (SFN) and Relaxation Theory (RT) has proved to achieve huge reduction in packet loss rates (as low as 0.014%) which also minimizes end-to-end delay (less than 150ms) within allowable WSN threshold.