Synchronization of delay for OTT services in LTE

Goldstein, A. B.; Zarubin, Anton; Onufrienko, A. V.; Elagin, Vasiliy S.; Belozertsev, I. A.

doi:10.1109/synchroinfo.2018.8456944

Cited by 8 publications

(4 citation statements)

References 3 publications

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“…MNOs are obliged [13] to collect the statistics of service quality rates for the aim of internal control (audit) within the limits of current enterprise quality control system.…”

Section: General Methods For Qoe and Qos Definitionmentioning

confidence: 99%

Method for QOE monitoring and increasing in cellular networks based on QOE-to-QOS mapping using spline approximation

Al-Azzeh

Одарченко²,

Abakumova

et al. 2022

J Wireless Com Network

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The current level of development of the cellular services market, qualitative changes in the means and methods of providing services, and the increased volume and diversity of information circulating in cellular networks have evoked the need for service quality assessment system improvement. To maintain competitiveness, the main efforts of operators are aimed at improving quality and increasing the service life of subscribers in the network by ensuring the required level of customer satisfaction in high-quality services through a system of organizational–technical and socioeconomic measures to bring the achieved level of quality-of-service (QoS) provision in accordance with the existing, emerging, or projected needs of subscribers. To achieve improved QoS provision, a functional relationship between network parameters has been established: The impact of key performance indicators on a key quality indicator through the use of cubic Hermitian splines (CHS) has been determined. The use of splines, as a signal model, can significantly improve the quality of signal processing due to the continuity of values and partial derivatives in the joints of spline gluing. CHS are characterized by calculation simplicity, as they provide high-speed computing, which, in turn, is important for real-time work when processing large data sets. Experimentally, it was shown that the use of splines allows for the ability to calculate statistical estimates of the required parameters of spline approximations, but also their confidence intervals, which increases the accuracy and probability of further calculations and is a distinct advantage of this approach. Also, the methods of service quality management through machine learning have been improved, which are effective tools for modeling integrated indicators of communication services quality control, monitoring their condition in terms of final copies of services, determining the causes of degradation, and reporting. It monitors the service performance provided by the cellular operator. Finally, the method checks the readiness and availability of services, detects network nodes through which quality degradation occurs, collects various quality metrics, and compares them with pre-installed quality indicators.

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“…MNOs are obliged [13] to collect the statistics of service quality rates for the aim of internal control (audit) within the limits of current enterprise quality control system.…”

Section: General Methods For Qoe and Qos Definitionmentioning

confidence: 99%

Method for QOE monitoring and increasing in cellular networks based on QOE-to-QOS mapping using spline approximation

Al-Azzeh

Одарченко²,

Abakumova

et al. 2022

J Wireless Com Network

View full text Add to dashboard Cite

show abstract

“…A completely theoretical approach devoid of experimental data is adopted. [12] Prediction of the QoE for over-the-top (OTT) services in LTE technologies and their corresponding effects.…”

Section: Referencementioning

confidence: 99%

“…As the development of the cellular service market continues to advance radically, spurring high levels of competition between MNOs, sophisticated methods that foster better service provision, better network coverage, and reductions in cell reselection, handover time, and requirements have been highly encouraged and adopted by MNOs [11]. Several works show the relevance of establishing different relationships between network parameters and the QoS provided via an optimization process [3,12].…”

Section: Introductionmentioning

confidence: 99%

Optimizing the Quality of Service of Mobile Broadband Networks for a Dense Urban Environment

Imoize,

Udeji,

Isabona

et al. 2023

Future Internet

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Mobile broadband (MBB) services in Lagos, Nigeria are marred with poor signal quality and inconsistent user experience, which can result in frustrated end-users and lost revenue for service providers. With the introduction of 5G, it is becoming more necessary for 4G LTE users to find ways of maximizing the technology while they await the installation and implementation of the new 5G networks. A comprehensive analysis of the quality of 4G LTE MBB services in three different locations in Lagos is performed. Minimal optimization techniques using particle swarm optimization (PSO) are used to propose solutions to the identified problems. A methodology that involves data collection, statistical analysis, and optimization techniques is adopted to measure key performance indicators (KPIs) for MBB services in the three locations: UNILAG, Ikorodu, and Oniru VI. The measured KPIs include reference signal received power (RSRP), reference signal received quality (RSRQ), received signal strength indicator (RSSI), and signal-to-noise ratio (SINR). Specific statistical analysis was performed, and the mean, standard deviation, skewness, and kurtosis were calculated for the measured KPIs. Additionally, the probability distribution functions for each KPI were plotted to infer the quality of MBB services in each location. Subsequently, the PSO algorithm was used to optimize the KPIs in each location, and the results were compared with the measured data to evaluate the effectiveness of the optimization. Generally, the optimization process results in an improvement in the quality of service (QoS) in the investigated environments. Findings also indicated that a single KPI, such as RSRP, is insufficient for assessing the quality of MBB services as perceived by end-users. Therefore, multiple KPIs should be considered instead, including RSRQ and RSSI. In order to improve MBB performance in Lagos, recommendations require mapping and replanning of network routes and hardware design. Additionally, it is clear that there is a significant difference in user experience between locations with good and poor reception and that consistency in signal values does not necessarily indicate a good user experience. Therefore, this study provides valuable insights and solutions for improving the quality of MBB services in Lagos and can help service providers better understand the needs and expectations of their end users.

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“…The network interaction process and traffic technical characteristics need to be identified to analyze the behavioral model [13,19]. It is also necessary to review the impact on the network due to the large number of transactions, because during the exchange process, the blockchain generates additional traffic to update the registries on all involved nodes, and there is an increased volume of service traffic that occurs when data is encrypted, which significantly reduces the proportion of useful traffic [20].…”

Section: Network Characteristics Of Blockchain Technologymentioning

confidence: 99%

Blockchain Behavioral Traffic Model as a Tool to Influence Service IT Security

et al. 2020

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The present article describes the behavioral model of blockchain services; their reliability is confirmed on the basis of experimental data. The authors identify the main technical characteristics and features associated with data transmission through the network. The authors determine the network scheme, working with blockchain transactions and the dependence of network characteristics on application parameters. They analyze the application of this model for the detection of the blockchain service and the possibility of the existing security mechanisms of this technology being evaded. Furthermore, the article offers recommendations for hiding the blockchain traffic profile to significantly complicate its identification in the data network.

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Synchronization of delay for OTT services in LTE

Cited by 8 publications

References 3 publications

Method for QOE monitoring and increasing in cellular networks based on QOE-to-QOS mapping using spline approximation

Method for QOE monitoring and increasing in cellular networks based on QOE-to-QOS mapping using spline approximation

Optimizing the Quality of Service of Mobile Broadband Networks for a Dense Urban Environment

Blockchain Behavioral Traffic Model as a Tool to Influence Service IT Security

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