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Open Internet Access: Measurement Methods and Impact of Qos Parameters on Service Performance

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (15 March 2022) | Viewed by 14727

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Special Issue Editor

Dr. Petr Koudelka

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Guest Editor

Czech Telecommunication Office, Sokolovska 58/219, 190 00 Prague, Czech Republic
Interests: 4G; 5G; IoT; signal coverage measurement methods; open internet (net neutrality)

Special Issue Information

The Open Internet access Regulation (EU) 2015/2120 requires, inter alia, a clear and comprehensible explanation of remedies in the event of any continuous or regularly recurring discrepancy between the actual performance of internet access service, regarding speed or other quality of service parameters, and the performance indicated. It is obvious that the actual performance of services is influenced by many factors: properties of access technologies, effects of physical phenomena, capacity of distribution or backhaul networks, traffic management, bandwidth (Mb/s) at the network termination point, QoS parameters, TCP congestion control, signal coverage and terminal interface standards.

Service performance measurement methods should take into account all of these factors, including the impact of established QoS parameter limits (NGN/NGA, Very High Capacity Networks, MEF technical specifications) and requirements for new modern electronic communications services (OTT services, video streaming, eHealth, Smart Home, online gaming, and also 5G-Car2Car2Infrastructure Communications).

This Special Issue of Sensors highlights measurement methods and procedures for determining service performance, advances in the development of available measurement tools, and statistical methods for examining the impact of a range of factors on service performance.

Dr. Petr Koudelka
Guest Editor

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Keywords

Open Internet access
QoS parameters
NGN/NGA
Very High Capacity Networks
Traffic management
Signal coverage
Service performance

Published Papers (6 papers)

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Research

18 pages, 1583 KiB

Open AccessArticle

Weigh-in-Motion: Lightweight Real-Time Identification of Gbps Wireless Traffic

by Sungsoo Kim, Joon Yoo and Jaehyuk Choi

Sensors 2022, 22(2), 437; https://0-doi-org.brum.beds.ac.uk/10.3390/s22020437 - 07 Jan 2022

Viewed by 1392

Abstract

Distinguishing between wireless and wired traffic in a network middlebox is an essential ingredient for numerous applications including security monitoring and quality-of-service (QoS) provisioning. The majority of existing approaches have exploited the greater delay statistics, such as round-trip-time and inter-packet arrival time, observed in wireless traffic to infer whether the traffic is originated from Ethernet (i.e., wired) or Wi-Fi (i.e., wireless) based on the assumption that the capacity of the wireless link is much slower than that of the wired link. However, this underlying assumption is no longer valid due to increases in wireless data rates over Gbps enabled by recent Wi-Fi technologies such as 802.11ac/ax. In this paper, we revisit the problem of identifying Wi-Fi traffic in network middleboxes as the wireless link capacity approaches the capacity of the wired. We present Weigh-in-Motion, a lightweight online detection scheme, that analyzes the traffic patterns observed at the middleboxes and infers whether the traffic is originated from high-speed Wi-Fi devices. To this end, we introduce the concept of ACKBunch that captures the unique characteristics of high-speed Wi-Fi, which is further utilized to distinguish whether the observed traffic is originated from a wired or wireless device. The effectiveness of the proposed scheme is evaluated via extensive real experiments, demonstrating its capability of accurately identifying wireless traffic from/to Gigabit 802.11 devices. Full article

(This article belongs to the Special Issue Open Internet Access: Measurement Methods and Impact of Qos Parameters on Service Performance)

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16 pages, 4512 KiB

Open AccessArticle

A Performance Benchmark for Dedicated Short-Range Communications and LTE-Based Cellular-V2X in the Context of Vehicle-to-Infrastructure Communication and Urban Scenarios

by Tibor Petrov, Lukas Sevcik, Peter Pocta and Milan Dado

Sensors 2021, 21(15), 5095; https://0-doi-org.brum.beds.ac.uk/10.3390/s21155095 - 28 Jul 2021

Cited by 16 | Viewed by 2674

Abstract

For more than a decade, communication systems based on the IEEE 802.11p technology—often referred to as Dedicated Short-Range Communications (DSRC)—have been considered a de facto industry standard for Vehicle-to-Infrastructure (V2I) communication. The technology, however, is often criticized for its poor scalability, its suboptimal channel access method, and the need to install additional roadside infrastructure. In 3GPP Release 14, the functionality of existing cellular networks has been extended to support V2X use cases in an attempt to address the well-known drawbacks of the DSRC. In this paper, we present a complex simulation study in order to benchmark both technologies in a V2I communication context and an urban scenario. In particular, we compare the DSRC, LTE in the infrastructural mode (LTE-I), and LTE Device-to-Device (LTE-D2D) mode 3 in terms of the average end-to-end delay and Packet Delivery Ratio (PDR) under varying communication conditions achieved through the variation of the communication perimeter, message generation frequency, and road traffic intensity. The obtained results are put into the context of the networking and connectivity requirements of the most popular V2I C-ITS services. The simulation results indicate that only the DSRC technology is able to support the investigated V2I communication scenarios without any major limitations, achieving an average end-to-end delay of less than 100 milliseconds and a PDR above 96% in all of the investigated simulation scenarios. The LTE-I is applicable for the most of the low-frequency V2I services in a limited communication perimeter (<600 m) and for lower traffic intensities (<1000 vehicles per hour), achieving a delay pf less than 500 milliseconds and a PDR of up to 92%. The LTE-D2D in mode 3 achieves too great of an end-to-end delay (above 1000 milliseconds) and a PDR below 72%; thus, it is not suitable for the V2I services under consideration in a perimeter larger than 200 m. Moreover, the LTE-D2D mode 3 is very sensitive to the distance between the transmitter and its serving eNodeB, which heavily impacts the PDR achieved. Full article

(This article belongs to the Special Issue Open Internet Access: Measurement Methods and Impact of Qos Parameters on Service Performance)

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17 pages, 2932 KiB

Open AccessArticle

A Method of Codec Comparison and Selection for Good Quality Video Transmission Over Limited-Bandwidth Networks

by Janusz Klink

Sensors 2021, 21(13), 4589; https://0-doi-org.brum.beds.ac.uk/10.3390/s21134589 - 04 Jul 2021

Cited by 8 | Viewed by 2907

Abstract

Finding a proper balance between video quality and the required bandwidth is an important issue, especially in networks of limited capacity. The problem of comparing the efficiency of video codecs and choosing the most suitable one in a specific situation has become very important. This paper proposes a method of comparing video codecs while also taking into account objective quality assessment metrics. The author shows the process of preparing video footage, assessing its quality, determining the rate–distortion curves, and calculating the bitrate saving for pairs of examined codecs. Thanks to the use of the spline interpolation method, the obtained results are better than those previously presented in the literature, and more resistant to the quality metric used. Full article

(This article belongs to the Special Issue Open Internet Access: Measurement Methods and Impact of Qos Parameters on Service Performance)

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14 pages, 2393 KiB

Open AccessArticle

Augmenting Speech Quality Estimation in Software-Defined Networking Using Machine Learning Algorithms

by Jan Rozhon, Filip Rezac, Jakub Jalowiczor and Ladislav Behan

Sensors 2021, 21(10), 3477; https://0-doi-org.brum.beds.ac.uk/10.3390/s21103477 - 17 May 2021

Cited by 1 | Viewed by 1727

Abstract

With the increased number of Software-Defined Networking (SDN) installations, the data centers of large service providers are becoming more and more agile in terms of network performance efficiency and flexibility. While SDN is an active and obvious trend in a modern data center design, the implications and possibilities it carries for effective and efficient network management are not yet fully explored and utilized. With most of the modern Internet traffic consisting of multimedia services and media-rich content sharing, the quality of multimedia communications is at the center of attention of many companies and research groups. Since SDN-enabled switches have an inherent feature of monitoring the flow statistics in terms of packets and bytes transmitted/lost, these devices can be utilized to monitor the essential statistics of the multimedia communications, allowing the provider to act in case of network failing to deliver the required service quality. The internal packet processing in the SDN switch enables the SDN controller to fetch the statistical information of the particular packet flow using the PacketIn and Multipart messages. This information, if preprocessed properly, can be used to estimate higher layer interpretation of the link quality and thus allowing to relate the provided quality of service (QoS) to the quality of user experience (QoE). This article discusses the experimental setup that can be used to estimate the quality of speech communication based on the information provided by the SDN controller. To achieve higher accuracy of the result, latency characteristics are added based on the exploiting of the dummy packet injection into the packet stream and/or RTCP packet analysis. The results of the experiment show that this innovative approach calculates the statistics of each individual RTP stream, and thus, we obtain a method for dynamic measurement of speech quality, where when quality decreases, it is possible to respond quickly by changing routing at the network level for each individual call. To improve the quality of call measurements, a Convolutional Neural Network (CNN) was also implemented. This model is based on two standard approaches to measuring the speech quality: PESQ and E-model. However, unlike PESQ/POLQA, the CNN-based model can take delay into account, and unlike the E-model, the resulting accuracy is much higher. Full article

(This article belongs to the Special Issue Open Internet Access: Measurement Methods and Impact of Qos Parameters on Service Performance)

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31 pages, 1764 KiB

Open AccessArticle

Adaptive Reservation of Network Resources According to Video Classification Scenes

by Lukas Sevcik and Miroslav Voznak

Sensors 2021, 21(6), 1949; https://0-doi-org.brum.beds.ac.uk/10.3390/s21061949 - 10 Mar 2021

Cited by 3 | Viewed by 1986

Abstract

Video quality evaluation needs a combined approach that includes subjective and objective metrics, testing, and monitoring of the network. This paper deals with the novel approach of mapping quality of service (QoS) to quality of experience (QoE) using QoE metrics to determine user satisfaction limits, and applying QoS tools to provide the minimum QoE expected by users. Our aim was to connect objective estimations of video quality with the subjective estimations. A comprehensive tool for the estimation of the subjective evaluation is proposed. This new idea is based on the evaluation and marking of video sequences using the sentinel flag derived from spatial information (SI) and temporal information (TI) in individual video frames. The authors of this paper created a video database for quality evaluation, and derived SI and TI from each video sequence for classifying the scenes. Video scenes from the database were evaluated by objective and subjective assessment. Based on the results, a new model for prediction of subjective quality is defined and presented in this paper. This quality is predicted using an artificial neural network based on the objective evaluation and the type of video sequences defined by qualitative parameters such as resolution, compression standard, and bitstream. Furthermore, the authors created an optimum mapping function to define the threshold for the variable bitrate setting based on the flag in the video, determining the type of scene in the proposed model. This function allows one to allocate a bitrate dynamically for a particular segment of the scene and maintains the desired quality. Our proposed model can help video service providers with the increasing the comfort of the end users. The variable bitstream ensures consistent video quality and customer satisfaction, while network resources are used effectively. The proposed model can also predict the appropriate bitrate based on the required quality of video sequences, defined using either objective or subjective assessment. Full article

(This article belongs to the Special Issue Open Internet Access: Measurement Methods and Impact of Qos Parameters on Service Performance)

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24 pages, 5405 KiB

Open AccessArticle

Voice Communication in Noisy Environments in a Smart House Using Hybrid LMS+ICA Algorithm

by Radek Martinek, Jan Vanus, Jan Nedoma, Michael Fridrich, Jaroslav Frnda and Aleksandra Kawala-Sterniuk

Sensors 2020, 20(21), 6022; https://0-doi-org.brum.beds.ac.uk/10.3390/s20216022 - 23 Oct 2020

Cited by 10 | Viewed by 3008

Abstract

This publication describes an innovative approach to voice control of operational and technical functions in a real Smart Home (SH) environment, where, for voice control within SH, it is necessary to provide robust technological systems for building automation and for technology visualization, software for recognition of individual voice commands, and a robust system for additive noise canceling. The KNX technology for building automation is used and described in the article. The LabVIEW SW tool is used for visualization, data connectivity to the speech recognizer, connection to the sound card, and the actual mathematical calculations within additive noise canceling. For the actual recognition of commands, the SW tool for recognition within the Microsoft Windows OS is used. In the article, the least mean squares algorithm (LMS) and independent component analysis (ICA) are used for additive noise canceling from the speech signal measured in a real SH environment. Within the proposed experiments, the success rate of voice command recognition for different types of additive interference (television, vacuum cleaner, washing machine, dishwasher, and fan) in the real SH environment was compared. The recognition success rate was greater than 95% for the selected experiments. Full article

(This article belongs to the Special Issue Open Internet Access: Measurement Methods and Impact of Qos Parameters on Service Performance)

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