CMT-SCTP and MPTCP Multipath Transport Protocols: A Comprehensive Review

Tomar, Parul; Kumar, Gyanendra; Verma, Lalit; Sharma, V.; Kanellopoulos, Dimitris; Rawat, Sur Singh; Alotaibi, Youseef

doi:10.3390/electronics11152384

Cited by 23 publications

(14 citation statements)

References 233 publications

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“…As more and more dataintensive video applications, such as ultra-high-definition video, AR/VR, and even high-resolution 3D holographic images enter mobile devices in the future, multipath technology has gradually become the focus of attention. However, the development of some multipath transmission protocols is limited due to their incompatibility with Network Address Translation (NAT) devices, such as the Concurrent Multipath Transfer for Stream Control Transmission Protocol (CMT-SCTP) based on SCTP extensions [10]. In addition, the deployment resistance of MultiPath TCP (MPTCP) based on TCP extension is very large, and most research is in path management and data scheduling [11].…”

Section: Related Workmentioning

confidence: 99%

Retracted: Anomaly detection with ensemble empirical mode decomposition and approximate entropy for quick user datagram protocol internet connection‐based distributed Blockchain systems

Cao

et al. 2023

IET Software

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With the vigorous development of mobile Internet and Blockchain, the rapid and secure interaction of high-frequency data in the era of data explosion has gradually become an urgent need for people. Quick User Datagram Protocol Internet Connection Protocol (QUIC) can be perfectly integrated into the Blockchain due to its low latency and high security, providing a safe and reliable transmission service for the Blockchain system. However, QUIC-based distributed Blockchain systems are vulnerable to cyberattacks due to asymmetric encryption and timestamp, which seriously impacts security and fairness. Therefore, based on the self-similarity of QUIC network traffic, this study proposes an anomaly detection model for QUIC network traffic based on Ensemble Empirical Mode Decomposition and Approximate Entropy. The model obtains several intrinsic mode functions and a residual term by decomposing the network traffic, introducing Approximate Entropy to judge the complexity of each component, and using the Hurst parameter to determine the generation of abnormal traffic. Compared with traditional detection methods, the model can effectively overcome the problems of poor adaptive ability and low efficiency and has high accuracy, which can be used for attack detection and prevention of network nodes. K E Y W O R D S computer network security, data flow analysis, software reliability, transport protocols 1 | INTRODUCTION Blockchain technology is an integrated and innovative application of various IT technologies. It is a technical solution for storing, verifying, transmitting, and exchanging network data without relying on a third party and its distributed nodes. It has two core characteristics: data is difficult to tamper with and decentralisation. Based on these two characteristics, the information recorded by the Blockchain is more authentic and reliable, which can help solve the problem of people's mutual distrust [1, 2]. It solves the problem of data trust and security through distributed ledgers, consensus mechanisms, smart contracts, authorisation, and encryption [3]. In recent years, Blockchain technology is continuously empowering various fields. Figure 1 shows a 5G wireless network and Blockchainbased network architecture. The architecture collects real-time data through the Internet of Things and uploads the data and events to the Blockchain platform, enabling secure scheduling of terminal devices connected to the 5G network [4]. Integrating 5G and Blockchain technology will open the era of inter-chain integration, which can provide an efficient, safe, and fast service experience. With the continuous development This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Related Workmentioning

confidence: 99%

Retracted: Anomaly detection with ensemble empirical mode decomposition and approximate entropy for quick user datagram protocol internet connection‐based distributed Blockchain systems

Cao

et al. 2023

IET Software

View full text Add to dashboard Cite

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“…In addition to this protocol it also keeps redundant paths for backup. A related study [16] also showed that different network configurations also agree that the performance of SCTP is better through several parameters. The study in the area of wireless sensor networks is carried by authors in [17].…”

Section: Literature Reviewmentioning

confidence: 81%

Comparative Analysis of TCP, TCP-Vegas, and SCTP in Mobile Ad-Hoc Networks

Mirani¹,

Kumar²,

Memon³

et al. 2022

JISR-C

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Mobile Ad hoc Networks (MANET) are a collection of mobiles and smart devices that communicate using wireless links. These types of networks are growing at the best speed and being used at a large scale than before ever because of their high availability and mobility. As the usage scale of MANET devices has been increasing, the challenges have also increased for example the proper delivery of data or information to every mobile node. Traditionally, transmission control protocol(TCP) is used for delivery but it does not fit in all scenarios due to some of its limitations such as network congestion and quick recovery in case of link failure. In this, a comparative analysis of TCP is performed with the stream control transmission protocol (SCTP) and a TCP variant called TCP VEGAS. A number of ad hoc Scenarios are proposed with varying numbers of mobile nodes,i.e 11,21, and 31. The results obtained indicate that SCTP outperforms TCP and VEGAS in throughput. The packet lifetime while using SCTP is also small i.e 0.19 seconds. The link utilization of SCTP is better than TCP and VEGAS. However, TCP increases its link utilization than VEGAS for the nodes in MANET of large delay.

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“…Model performance was quantified by evaluating precision, recall, F1-score, and accuracy. The implementation was performed with the help of the Scikit-Learn library [63][64][65][66]. 2 shows the comparison of results of the multi-tier and single-tier models.…”

Section: Implementation Of Multi-tier Modelmentioning

confidence: 99%

Multi-Tier Sentiment Analysis of Social Media Text Using Supervised Machine Learning

Tariq¹,

Masood²,

Subahi³

et al. 2023

Computers, Materials &Amp; Continua

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Sentiment Analysis (SA) is often referred to as opinion mining. It is defined as the extraction, identification, or characterization of the sentiment from text. Generally, the sentiment of a textual document is classified into binary classes i.e., positive and negative. However, fine-grained classification provides a better insight into the sentiments. The downside is that fine-grained classification is more challenging as compared to binary. On the contrary, performance deteriorates significantly in the case of multi-class classification. In this study, pre-processing techniques and machine learning models for the multi-class classification of sentiments were explored. To augment the performance, a multi-layer classification model has been proposed. Owing to similitude with social media text, the movie reviews dataset has been used for the implementation. Supervised machine learning models namely Decision Tree, Support Vector Machine, and Naïve Bayes models have been implemented for the task of sentiment classification. We have compared the models of single-layer architecture with multi-tier model. The results of Multi-tier model have slight improvement over the single-layer architecture. Moreover, multi-tier models have better recall which allow our proposed model to learn more context. We have discussed certain shortcomings of the model that will help researchers to design multi-tier models with more contextual information.

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CMT-SCTP and MPTCP Multipath Transport Protocols: A Comprehensive Review

Cited by 23 publications

References 233 publications

Retracted: Anomaly detection with ensemble empirical mode decomposition and approximate entropy for quick user datagram protocol internet connection‐based distributed Blockchain systems

Retracted: Anomaly detection with ensemble empirical mode decomposition and approximate entropy for quick user datagram protocol internet connection‐based distributed Blockchain systems

Comparative Analysis of TCP, TCP-Vegas, and SCTP in Mobile Ad-Hoc Networks

Multi-Tier Sentiment Analysis of Social Media Text Using Supervised Machine Learning

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