Improvement of TCP Vegas algorithm based on forward direction delay

Guan, Shijie; Jiang, Yueqiu; Guan, Qixue

doi:10.1504/ijwet.2020.107690

Cited by 6 publications

(8 citation statements)

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“…Because the ear cochlea contains filtering qualities, it may map various frequencies to different places on the basilar membrane, which allows for more accurate mapping. As a result, the cochlea is often referred to as a filter bank [ 21 ]. Psychologists were able to acquire a set of filter banks comparable to the cochlear effect via psychological research, which they named the Mel frequency filter bank, based on this characteristic.…”

Section: Proposed Workmentioning

confidence: 99%

“…Figure 8 shows the throughput comparison between the present and proposed methods. We compared the throughput of the proposed system with that of TCP [ 19 ], SACK [ 20 ] TCP vegas[ 21 ], and SCTP [ 23 ]. The graph clearly shows that the recommended strategy has a higher throughput of 700 for 80 nodes than traditional techniques.…”

Section: Performance Analysismentioning

confidence: 99%

“…Figure 9 depicts a side-by-side comparison of the average delay for the present and proposed techniques. We compared the average delay of the proposed system with that of TCP [ 19 ], SACK [ 20 ] TCP vegas [ 21 ], and SCTP [ 23 ]. The graph shows that the suggested process transmits data with the least latency compared to conventional methods.…”

Section: Performance Analysismentioning

confidence: 99%

“…The comparison of packet delivery ratios for the proposed and existing methods is shown in Figure 10 . The average packet delivery ratio of the proposed system is compared with that of TCP [ 19 ], SACK [ 20 ] TCP vegas [ 21 ], and SCTP [ 23 ]. It is evident that the proposed technique has a higher average packet delivery ratio than the existing methods which confirms the superiority of the proposed method.…”

Section: Performance Analysismentioning

confidence: 99%

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Innovative Practice of Music Education in the Universities in the Context of 5G Network

Huang

2022

Computational Intelligence and Neuroscience

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Music education is among the most significant subjects covered in providing high-quality education in Chinese universities and colleges. Music education is critical to providing high-quality education to students. It contributes significantly to the development of students’ creative motivation, inventive capacity, and personality development. Music education provides excellent outcomes in music instruction and fosters students’ original thinking and comprehensive abilities, and therefore supports the overall development of high-quality education. With the development of the educational system, it is becoming more vital to teach students a high level of musical literacy. With the advent of 5G mobile communication, it will become one of the core technologies in Chinese music education, providing an innovative framework for music education. In this study, a novel music education model is proposed for the development of music education using the GTZAN dataset which is comprised of 100 distinct specimens for every genre and ten various kinds of music. The dataset is normalized to prepare it for further processing and the characteristics of the song are retrieved using a technique called spectrum-based feature extraction (SBF). Bi-recurrent neural networks (Bi-RNN). are used to classify objects in space. An improved TCP congestion control algorithm (ITCCA) is proposed for efficient data transmission between the 5G networks. To optimize the performance of the transmission protocol, the honey bee optimization algorithm is employed. The performance of the proposed model is examined and contrasted with that of the currently used approaches. The proposed model shows high performance in terms of throughput, average delay, and packet delivery ratio. The model has the potential to successfully integrate 5G technologies and music education and provide the students with rich and diversified teaching materials and flexible instructional formats.

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Section: Proposed Workmentioning

confidence: 99%

Section: Performance Analysismentioning

confidence: 99%

Section: Performance Analysismentioning

confidence: 99%

Section: Performance Analysismentioning

confidence: 99%

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Innovative Practice of Music Education in the Universities in the Context of 5G Network

Huang

2022

Computational Intelligence and Neuroscience

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“…FAST-TCP [6] and TCP-Vegas [7] are examples in this regard. Nevertheless, it is indicated that they have strictly corrupted behaviours when competing with loss-based TCP protocols.…”

Section: Introduction Tcp (Transmission Control Protocolmentioning

confidence: 99%

Congestion control in high‐speed networks using the probabilistic estimation approach

Jamali

Talebi

Fotohi

2021

Int J Communication

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Summary Nowadays, the bulk of Internet traffic uses Transmission Control Protocol (TCP) for reliable transmission. But the standard TCP's performance is very poor in high‐speed networks (HSNs), and hence, the core gigabytes links are usually underutilization. This problem has roots in conservative nature of TCP, especially in its Additive Increase Multiplicative Decrease (AIMD) phase. In other words, since TCP cannot figure out precisely the congestion status of the network, it follows a conservative strategy to keep the network from overwhelming. We believe that precisely congestion estimation in the network can solve this problem by avoiding unnecessary conservation. To this end, this paper proposes an algorithm, which considers packet loss and delay information jointly and employs a probabilistic approach to accurately estimation of congestion status in the network. To examine the proposed scheme performance, extensive simulations have been performed in the NS‐2 environment. Simulation results reveal that the proposed algorithm has better performance than existing algorithms in terms of bottleneck utilization, stability, throughput, and fairness.

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