A novel congestion detection and avoidance algorithm for multiple class of traffic in sensor network

Abstract

Congestion in a Wireless Sensor Network (WSN) can cause packet loss, low energy efficiency, and long delay. Moreover, some applications, e.g. multimedia and image, need to transmit large volumes of data concurrently from several sensors. These applications have different delay and QoS requirements. Congestion problem is more significant in such applications. To address this challenge, we propose an energy efficient congestion control scheme for sensor networks called ECODA (Enhanced Congestion Detection and Avoidance) which comprises two mechanisms: (i) Use dual buffer thresholds and weighted buffer difference for congestion detection; (ii) Dynamically estimate channel loading and optimize channel utilization. Simulations show that ECODA achieves efficient congestion control and flexible weighted fairness for different class of traffic. Therefore it leads to higher energy efficiency and better QoS in terms of throughput, fairness, and delay.