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Fuzzy Linguistic Knowledge for Active Queue Management in Wireless Ad-Hoc Networks
Abstract
Mobile ad-hoc network is a network without infrastructure, where every node has its own protocols and services for powerful cooperation in the network. Every node also has the ability to handle the congestion in its queues during traffic overflow. Traditionally, this was done through Drop-Tail policy, where the node drops the incoming packets to its queues during overflow condition. Many studies showed that early dropping of incoming packet is an effective technique to avoid congestion and to minimize the packet latency. Such an approach is known as Active Queue Management (AQM). In this chapter an enhanced algorithm, called Fuzzy-AQM, is suggested using fuzzy logic system to achieve the benefits of AQM. Uncertainty associated with queue congestion estimation and lack of mathematical model for estimating the time to start dropping incoming packets makes the Fuzzy-AQM algorithm the best choice. Extensive performance analysis via simulation showed the effectiveness of the proposed method for congestion detection and avoidance improving overall network performance.
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