2017
DOI: 10.1142/s1469026817500237
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Fuzzy Logic-Based Quality of Service Evaluation for Multimedia Transmission over Wireless Ad Hoc Networks

Abstract: This paper proposes a fuzzy logic (FL) model for evaluation of quality of service (QoS) in multimedia transmission over ad hoc networks as an effective mechanism for QoS management. It aims at minimizing the negative effects of major QoS parameters, (jitter, delay, packet loss) sustaining efficiency and reliability of data deliveries and improving overall system performance. Both triangular membership function (TMF) and Gaussian membership function (GMF) are adopted to demonstrate their effects in FL-QoS evalu… Show more

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Cited by 6 publications
(4 citation statements)
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“…Such approaches should be improved to be suitable with the WSN in IoT medium. Thence, a novel neuro-fuzzy rule based cluster formation and routing protocol to perform effective routing at IoT based WSNs [30]. The proposed algorithm is based on operation with classical WSAN and checks the performance specification with a neuro-fuzzy control system as in Figure 4.…”
Section: Neural Fuzzy Approach For Link Qualitymentioning
confidence: 99%
“…Such approaches should be improved to be suitable with the WSN in IoT medium. Thence, a novel neuro-fuzzy rule based cluster formation and routing protocol to perform effective routing at IoT based WSNs [30]. The proposed algorithm is based on operation with classical WSAN and checks the performance specification with a neuro-fuzzy control system as in Figure 4.…”
Section: Neural Fuzzy Approach For Link Qualitymentioning
confidence: 99%
“…They have been applied to solving many different real-world problems such as classification, regression, control, decision making, prediction, etc. [6][7][8][9][10][11][12].…”
Section: Introductionmentioning
confidence: 99%
“…A T1FL system is made up of fuzzifier, rule-base, fuzzy inference engine, and defuzzification units. It has been applied in many scientific and engineering fields, including social science in the area of politics [17] [25]. However, T1FL has limited capabilities to directly and adequately handle uncertainties and imprecision because the T1F set has a membership grade that is crisp.…”
Section: Introductionmentioning
confidence: 99%
“…Additionally, PSO adjusts a few parameters, a slight modification of one version could well be employed in a wide variety of applications. PSO has been used to solve a wide range of problems across many applications, including, fuzzy controllers design[25] [36].…”
mentioning
confidence: 99%