Using fuzzy link cost and dynamic choice of link quality metrics to achieve QoS and QoE in wireless mesh networks

Abstract

The growth of multimedia applications and wireless systems requires a new behavior of routing protocols for Wireless Mesh Networks (WMNs). It is necessary to provide not only the minimum requirements for Quality of Service (QoS), but also to assure the Quality of Experience (QoE) support for multimedia applications. In this context, the usage of only one link quality metric for routing different types of packets within the network is not enough to ensure applications with suitable QoS and QoE levels. This paper presents a variation of the WMN routing protocol Optimized Link State Routing (OLSR), to achieve QoS and QoE requirements for multimedia applications. It is based on the dynamic choice of metrics and in a Fuzzy Link Cost (FLC) to determine the best routes for multimedia packets. The proposed FLC metric is based on a fuzzy system that uses two link quality metrics, namely Expected Transmission Count (ETX) and Minimum Delay (MD), to define a new metric. Simulations were performed to demonstrate the performance of the proposed metric compared to the ones present in the original OLSR and other current versions of this protocol. For comparison purposes, it was considered different performance evaluation QoS metrics and the quality of videos received by the user in a higher competition scenario.

A Modified Fuzzy Logic Routing for Wireless Mesh Network

“…The performance ratio of fuzzy oblivious routing is better than oblivious routing it is plotted for each hour since the beginning of the trace collection. The ratio generally remains in the range, high on the other performance, with irregular conditions on the network [12]. This result shows that our fuzzy oblivious routing strategy performs competitively against the oracle routing strategy even without the knowledge of attack based demand on this wireless network.…”

“…Fuzzy Logic introduced by Zadeh [12] allows a computer to model the same way that people do, not always precise. People think and reason using their terms such as "hot" and "fast", rather than in exact numerical terms 90 degrees and 200 km/hours respectively.…”