An Adaptive Proportional Integral Active Queue Management Algorithm based on Self-Similar Traffic Rate Estimation in WSN

• Heng Liu,
• Yan Wang,

Vol. 5, No. 11, November 28, 2011
10.3837/tiis.2011.11.004, Download Paper (Free):

• Self-similar
• QoS
• traffic rate estimation
• Active Queue Management
• WSN

Abstract

Wireless Sensor Network (WSN) is made up of a number of sensor nodes and base stations. Traffic flow in WSN appears self-similar due to its data delivery process, and this impacts queue length greatly and makes queuing delay worse. Active queue management can be designed to improve QoS performance for WSN. In this paper, we propose self-similar traffic rate estimating algorithm named Power-Law Moving Averaging (PLMA) to regulate packet marking probability. This algorithm improves the availability of the rate estimation algorithm under the self-similar traffic condition. Then, we propose an adaptive Proportional Integral algorithm (SSPI) based on the estimation of the Self-Similar traffic rate by PLMA. Simulation results show that SSPI can achieve lower queue length jitter and smaller setting time than PI.

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