Traffic Quality Of Service Research Articles

The concept of effective coverage radius use of the unlicensed high-frequency range in the operation of the 5G network

Economic expediency encourages mobile operators to deploy 5G networks in places with a high concentration of speed-demanding subscribers. In such conditions, sharp fluctuations in the volume of traffic with regulated requirements for the quality of service are inevitable. Note that 5G operates in the millimeter range. Accordingly, the quality of traffic service is affected both by the number of subscribers simultaneously initiating requests from one sector of coverage, and by the appearance of obstacles opaque to radio radiation in the space between the subscriber device and the base station. Effective smoothing of 5G traffic fluctuations, taking into account these disturbing factors, is an urgent task. The goal of this research is to evaluate the service quality parameters in a target area characterized by a specific user density. It takes into account that if the declared QoS requirements for connection speed for users in a network segment deployed within the licensed frequency range for 5G are not met, they can utilize a network segment deployed in the unlicensed high-frequency range for 5G under conditions of free competition. The metric being studied is the probability of session loss in the licensed network segment and the achievable transmission speed in the unlicensed network segment. Based on this, a method for assessing the density of base station deployment in the unlicensed network segment necessary to support the specified user density in the licensed network segment with defined QoS guarantees in terms of bandwidth is formalized. The experiment results showed that the probability of losing sessions with regulated requirements for the quality of service in both network segments, in addition to the base station placement density and subscriber devices, is significantly affected by the minimum data transfer rate, the intensity of obstacles, and the value of the Contention Window.

Model and Methods of Traffic Routing in a Communication Network Using UAVs

Relevance. The development of 5G networks and subsequent generations is accompanied by the development of new services, in particular, virtual, augmented reality services, as well as telepresence, as well as radio access networks. In particular, there is an increase in operating frequencies, which poses additional challenges for organizing a network that can meet the requirements for the quality of traffic service from new services and ensure the availability of communication to users. These problems can be solved by various methods of placing access points, including using UAVs. This approach ensures the efficiency of construction and flexibility of the access network structure, but also requires the use of methods for placing access points in relation to users and other elements of the communication network. Problem statement: development of methods for placing routers in a UAV swarm and selecting traffic routes when organizing an access network, in order to improve the efficiency of the communication network. Purpose of the work: improving the efficiency of building an access network using UAVs through the development of clustering methods and distributing routers in a UAV swarm. Methods. The studies were carried out using the provisions of information theory, mathematical optimization methods, graph theory methods and clustering methods. The numerical results were obtained using the numerical simulation method in Python. Result. The developed model and methods allow for the distribution of network routers (access points) located on UAVs taking into account the quality of service and ensuring the construction of a connected mesh network and its connection with the mobile network, which can be used in both modern and future communication networks. Novelty: a modeling and methodological apparatus has been developed that allows for increasing the efficiency of building wireless access networks using UAVs, in particular, allowing for selecting the placement positions of routers in a UAV swarm and the logical structure of the network. The developed modeling and methodological apparatus solves the problem of traffic routing taking into account the quality of its service. Practical significance: the proposed model and methods can be used to organize service in 5G networks and subsequent generations. In particular, they allow for ensuring the availability of communication and the efficiency of network organization in cases of insufficient coverage, as well as in cases of failure of individual network elements. The ability to unload traffic to a local network allows for improving the quality of traffic service in the operator's network.

Is traffic police SERVQUAL assessment different among drivers in terms of experience?

Designing tailored services is critical to enhancing client satisfaction for private and public services such as road traffic. Among the factors associated with car accidents are traffic violations of established rules and regulations. Indeed, driving skills and practice have become crucial in a complex and dynamic road environment. The study’s objective was to advise traffic department managers on how to customize their service for drivers regarding their experience. A questionnaire assessing their expectations and perceived performance with regard to six traffic service quality dimensions, namely tangibility, reliability, promptitude, responsiveness, assurance, and empathy, was self-administered to 886 motorists chosen using a simple random sampling technique in the Philippines and South Africa. Data collected were analyzed using ANOVA and Post Hoc Tuckey HSD. Results indicate that less experienced drivers had a better appreciation of traffic service quality provided by traffic departments and officers. Therefore, more focus should be placed on experienced drivers to raise their level of satisfaction.

An Efficient and Privacy-Preserving Information Reporting Framework for Traffic Monitoring in Vehicular Networks

Traffic monitoring services show great potential for improving traffic efficiency in vehicular networks. With the assistance of 5G innovation, vehicles can report information such as driving misbehavior and traffic status to the traffic monitoring server which then returns feedback to the network to enhance the efficiency of traffic management. However, some challenging issues in information reporting need to be addressed first. Trivial reported information significantly increases the workload of the server. Moreover, a server is difficult to distinguish the truth of reported messages. As a result, the server is incapable of returning immediate feedback to the network, thereby reducing the quality of traffic services. Meanwhile, uploading location-based information to the server exposes vehicles' privacy. Although some existing techniques such as trust management benefit information reporting, a complete framework is still missing. In this paper, we propose an information reporting framework for solving both efficiency and privacy issues. Specifically, messages are probabilistically reported to the server depending on their importance. Furthermore, the DAG-based blockchain ensures that messages reported for a specific event are all gathered in the same ledger. We also present a scheme based on the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">geo-indistinguishability</i> to protect the location privacy of vehicles. Extensive experiments demonstrate that the proposed framework preserves the location privacy of vehicles and achieves efficiency with acceptable overheads.

Effect of service differentiation on QoS in IEEE 802.11e enhanced distributed channel access: a simulation approach

The enhanced distributed channel access (EDCA) protocol is a supplement to IEEE 802.11 medium access control (MAC), ratified by IEEE 802.11e task group to support quality of service (QoS) requirements of both data and real-time applications. Previous research show that it supports priority scheme for multimedia traffic but strict QoS is not guaranteed. This can be attributed to inappropriate tuning of the medium access parameters. Thus, an in-depth analysis of the EDCA protocol and ways of tuning medium access parameters to improve QoS requirements for multimedia traffic is presented in this work. An EDCA model was developed and simulated using MATLAB to assess the effect of differentiating contention window (CW) and arbitration inter-frame space (AIFS) of different traffic on QoS parameters. The optimal performance, delay, and maximum sustainable throughput for each traffic type were computed under saturation load. Insight shows that traffic with higher priority values acquired most of the available channels and starved traffic with lower priority values. The AIFS has more influence on the QoS of EDCA protocol. It was also observed that small CW values generate higher packet drops and collision rate probability. Thus, EDCA protocol provides mechanism for service differentiation which strongly depends on channel access parameters: CW sizes and AIFS.

QoS Provisioning in Space Information Networks: Applications, Challenges, Architectures, and Solutions

In emerging scenarios such as the Internet of Things and space-and-ground integrated networks, diverse new applications bring multi-di-mensional quality of service (QoS) requirements to space information networks (SINs). As a mixed problem of routing, traffic control, and resource allocation, QoS provisioning is concentrated on providing customized QoS guarantee to SIN users. On the other hand, motivated by the recent progress in technologies such as software-defined networking and machine learning, many potential solutions for QoS provisioning have been proposed. To utilize the state-of-the-art approaches within QoS provisioning, we provide a forward-looking vision of QoS provisioning that outlines the applications, challenges, architectures, and associated solutions. In this article, we first introduce the applications in three emerging scenarios in terms of traffic characteristics and QoS requirements and identify the accompanying technical challenges for SINs. Then a QoS provisioning architecture with two differentiated transmission modes is proposed. The mirror source mode for bandwidth-tolerant flows improves the network efficiency by centralized traffic scheduling. The preemptive mode for bandwidth-sensitive flows reduces the end-to-end delay by edge node control. Furthermore, the enabling technologies and potential solutions for control logic and forwarding mechanism are analyzed. At last, future research directions are discussed.

Improving Throughput in Sub – Nyquist Spectrum Sensing using a Cluster Model for Cognitive Radio Networks

The underutilization of radio spectrum has led to the downfall of Fixed Spectrum Allocation (FSA) since mobile frequency bands are getting overloaded due to rise of users all across the world. These drawbacks could be overcome by a concept called Dynamic Spectrum Allocation (DSA) implemented by an intelligent form of communication termed as Cognitive Radio Networks (CRN). CRN finds its applications adopted in military for battlefield surveillance, medical areas for 24 × 7 patient monitoring and also in TV white spaces. CRN involves SS in an efficient manner to deploy mobile users in TV frequency bands in a wider range through Wideband SS (WSS). WSS provides omnipresent spectrum monitoring for detecting spectral holes in the unutilized TV spectrum. The concept of Sub-Nyquist Sensing in WSS has several advantages in data sampling improving a plethora of application throughputs. The cluster approach in CRN has improved the base station crisis in load handling, throughput performance. In this paper, we focus on improving the traffic Quality of service (QoS) of the users in WSS by employing a cluster CRN network and applying Nyquist Sensing (NS) and Sub-Nyquist sensing (SNS) to find out the significance of SNS in the cluster network.

Construction and Application of Cloud Platform for Urban Rail Transit

&lt;p&gt;Rail transit is a new form of transportation in the process of modern urban development. It has a far-reaching impact on improving urban traffic environment, relieving urban traffic pressure and improving urban traffic service quality. The rail transit cloud platform is an important part of modern rail transit, and it is also a key factor related to the construction quality of urban rail transit. In this paper, the current situation of construction and application of urban rail transit cloud platform are introduced in detail, and the related standard compilation of urban rail transit cloud platform, achievements in the development and construction process, construction mode, index establishment, acceptance process optimization, cloud operation and maintenance system establishment and other issues are systematically expounded. According to the technical drive and standard compilation of urban rail transit cloud platform, the development of urban rail transit cloud platform is prospected.&lt;/p&gt;

A SDN-based active measurement method to traffic QoS sensing for smart network access

Power communication network is very important for the management of the power system. With the exponential growth of the power equipment and the drastic increase in the amount of power monitoring data, there is a huge challenge for the smart network access of the power communication network. Then, software defined network (SDN) which is flexible and scalable is suitable for the power communication network. In order to increase the high quality of service (QoS) of provided communication for users, the traffic QoS sensing is the key of the smart network access in the power communication network. Then, we propose a SDN-Based active measurement method to measure the evaluation parameters of the smart network access in the power communication network. Firstly, we introduce the instructions provided by the OpenFlow protocol, which can be used to collect statistics from OpenFlow switches. Secondly, we define the parameters that should be measured in the power communication network to evaluate the performance of the network and give the corresponding measurement method with them. Next, we proposed a SDN-based active measurement algorithm that updates its measurement interval based on the measurement throughput changes. Finally, we built a simulation platform using the Mininet simulator and the POX controller to verify the proposed measurement method, and the simulation results show the accuracy of our proposed method and the measurement load of our proposed method are both better than that of Polling measurement methods.

Centralized Trust-Based In-Band Control for SDN Control Channel

In SDN architecture, the control channel between the control and data planes is extremely significant, which has two connection modes: out-of-band mode and in-band mode. For in-band mode, the key to the establishment of SDN control channel is how to forward in-band control traffic in the data plane (control traffic: traffic between controllers and switches). In almost all the existing implementation of the in-band SDN networks, the forwarding of in-band control traffic in the data plane depends on distributed Layer 2 switching that cannot respond to the network state change immediately. In this article, we propose a Centralized Trust-based In-Band (CTIB) control mechanism for SDN in-band control channel. Then based on CTIB control mechanism, we design CTIB routing algorithm to select the most trusted control path for each data plane switch in order to improve the QoS (Quality of Service) of in-band control traffic. Furthermore, we implement CTIB control mechanism in an in-band SDN network and carry out several experiments to test the QoS of the in-band control traffic. The results indicate that there is a huge improvement of in-band control traffic QoS when using CTIB control mechanism compared to the distributed Layer 2 switching.

ИСПОЛЬЗОВАНИЕ СПЛАЙН-ЭКСТРАПОЛЯЦИИ ДЛЯ ПОВЫШЕНИЯ ПОКАЗАТЕЛЕЙ КАЧЕСТВА ТЕЛЕКОММУНИКАЦИОННЫХ СИСТЕМ

The problem of predicting self-similar traffic with significant and frequent ripples and the property of long-term dependence is considered. For short-term prediction of self-similar traffic, which is performed outside the considered time interval, a method of spline extrapolation based on various spline functions (cubic and cubic B-splines) is proposed. We recommend a method for estimating traffic prediction errors for each traffic prediction option using cubic or cubic B-splines. Comparison of the results of predicting self-similar traffic using various spline functions (cubic and cubic B-splines) show that the accuracy of the prediction can be improved by using cubic B-splines. According to the results of the study, it is established that cubic B-splines are characterized by high constructively, adequacy to the tasks and simplicity of practical implementation. Their use makes it possible to greatly simplify computational processes using formalized mathematical constructs. The use of the proposed method of spline extrapolation based on cubic B-splines has several advantages over other known methods, namely, ease of practical implementation, high accuracy of forecasting, the ability to accurately extrapolate peak "bursts" of traffic, which is especially important when solving problems in real time. The results of predicting self-similar traffic will allow the operator, at the stage of design and further operation of the mobile communication network, to provide the required amount of buffer devices for the network hardware and software, thereby avoiding network congestion and exceeding standard values of traffic service quality indicators. Proposed is the prospect of further research through the use of wavelet-extrapolation in order to improve the accuracy of prediction. Practical significance is determined by the developed recommendations for using the spline-extrapolation method in solving various problems of designing networks of various technologies and structures.

Analysis of traffic offload using multi‐attribute decision making technique in heterogeneous shared networks

Over the years, the authors have witnessed tremendous growth in mobile data traffic. To address the capacity requirements, the mobile network operators (MNOs) are adding more radio nodes and spectrum layers. The spectrum layers vary in quality of service (QoS), utilisation and usage fee. To save operational costs, the MNOs could share their radio networks. The MNOs, therefore, should consider spectrum availability, link utilisation, link usage costs, traffic handling priorities and QoS for selecting the Donor link for traffic offload. In this study, the traffic offload scenario with multiple Donor links from different MNOs is analysed. The authors define the relevant queuing parameters for Donor link selection. Two hybrid multi-attribute decision-making (MADM) techniques, namely, (a) analytical hierarchical process (AHP) with grey relational analysis (GRA) technique and (b) entropy with range of values (RoV) technique for dynamic Donor link selection in traffic offload scenario and assess their benefits were compared. The authors use IP network measurements to derive the packet service time. It is observed that both the techniques Entropy-RoV and AHP-GRA align well with the dynamism of the network, though Entropy-RoV method performed without any pre-configuration. The AHP-GRA technique requires pre-configuration of parameters and when configured suitably, it can perform as a load equalisation technique.

KORELASI INDIKATOR PENILAIAN PEMERINGKATAN WEBSITE PERGURUAN TINGGI WEBOMETRICS DAN 4ICU

Colleges in Indonesia as part of an educational institution that seeks to improve the competitiveness of globally through the utilization of ICT (information and communication technology) has been aware of the importance of the website as a key component of the assessment in an effort to align ourselves as a global standard of the College. The instruments most frequently used by universities as reference materials to evaluate performance and productivity based on his/her website is through a college assessor database world, including Webometrics and 4ICU. Correlation between linking Webometrics and 4ICU are aimed to assist colleges in analyzing the quality of traffic services in the field of scientific publications in order to be able to compete in the global sphere and certainly for the better. The methodology used by using spearman rank correlation against major # 29 University according to the webometrics ranking based on 4ICU and 29 top-rated website 4ICU. The results of the research there is a relationship or a significant correlation between the webometrics ranking indicator with indicator correlation value 4ICU ranking of 0.591 contains the category strong enough.

Dynamic Radio Resource Slicing for a Two-Tier Heterogeneous Wireless Network

In this paper, a dynamic radio resource slicing framework is presented for a two-tier heterogeneous wireless network. Through software-defined networking-enabled wireless network function virtualization, radio spectrum resources of heterogeneous wireless networks are partitioned into different bandwidth slices for different base stations (BSs). This framework facilitates spectrum sharing among heterogeneous BSs and achieves differentiated quality-of-service (QoS) provisioning for data service and machine-to-machine service in the presence of network load dynamics. To determine the set of optimal bandwidth slicing ratios and optimal BS-device association patterns, a network utility maximization problem is formulated with the consideration of different traffic statistics and QoS requirements, location distribution for end devices, varying device locations, load conditions in each cell, and intercell interference. For tractability, the optimization problem is transformed to a biconcave maximization problem. An alternative concave search (ACS) algorithm is then designed to solve for a set of partial optimal solutions. Simulation results verify the convergence property and display low complexity of the ACS algorithm. It is demonstrated that the proposed radio resource slicing framework outperforms the two other resource slicing schemes in terms of low communication overhead, high spectrum utilization, and high aggregate network utility.

Smart Multi-RAT Access Based on Multiagent Reinforcement Learning

The ongoing increasing traffic in the era of big data yields unprecedented demands in user experience and network capacity expansion. The users of next generation mobile networks (5 G) should be able to use 3GPP, IEEE, and other technologies simultaneously. The integration of multiple radio access technologies (RATs) of licensed or unlicensed bands has been widely deemed as a cost-efficient way to greatly increase the network capacity. In this paper, we propose a smart aggregated RAT access (SARA) strategy with aim of maximizing the long-term network throughput while meeting diverse traffic quality of service (QoS) requirements. We consider the scenario that users with different QoS requirements access to a heterogeneous network with coexisting cellular-WiFi. In order to maximize system throughput while meeting diverse traffic QoS requirements in such a complex and dynamic environment, we exploit multiagent reinforcement learning to perform RAT selection in conjunction with resource allocation for individual user access requests, through sensing dynamic channel states and traffic QoS requirements. In SARA, we first use Nash Q-learning to provide a set of feasible RAT selection strategies while decreasing the strategy space in learning process, and then employ Monte Carlo tree search (MCTS) based Q-learning to perform resource allocation. Numerical results reveal that the network throughput can be maximized while meeting various traffic QoS requirements with limited number of searches by using our proposed SARA algorithm. For bulk arrival access requests, a suboptimal solution can be obtained as high computational complexity is incurred for achieving global optimality. Another attractive feature of SARA is that a tradeoff between the solution optimality and learning time can be readily made by terminating the search of MCTS according to the time constraint. Compared with traditional WiFi offloading schemes, SARA can significantly improve network throughput while guaranteeing traffic QoS requirements.

Applying Big Data, Machine Learning, and SDN/NFV for 5G Early-Stage Traffic Classification and Network QoS Control

Due to the rapid growth of mobile broadband and IoT applications, the early-stage mobile traffic classification becomes more important for traffic engineering to guarantee Quality of Service (QoS), implement resource management, and network security. Therefore, identifying traffic flows based on a few packets during the early state has attracted attention in both academic and industrial fields. However, a powerful and flexible platform to handle millions of traffic flows is still challenging. This study aims to demonstrate how to integrate various state-of-the-art machine learning (ML) algorithms, big data analytics platforms, software-defined networking (SDN), and network functions virtualization (NFV) to build a comprehensive framework for developing future 5G SON applications. This platform successfully collected, stored, analyzed, and identified a huge number of real-time traffic flows at broadband Mobile Lab (BML), National Chiao Tung University (NCTU). Moreover, we also implemented network QoS control to configure priorities per-flow traffic to enable bandwidth guarantees for each application by using SDN. Finally, the performance of the proposed models was evaluated by applying them to a real testbed environment. The powerful computing capacity of the platform was also analyzed.

Service-Oriented Cooperation Models and Mechanisms for Heterogeneous Driverless Vehicles at Continuous Static Critical Sections

As driverless vehicles are increasingly becoming possible, so does the use of such vehicles as intelligent carriers in different domains. Intelligent transportation systems (ITSs) show increasingly heterogeneous, cyber-physical, cooperative, and service-oriented features and are beginning to be merged with the emerging cyber-physical-social systems. Given this new trend, how to make these intelligent vehicles cooperate more safely and efficiently with one another according to novel constraints, such as mission type and quality-of-service (QoS), has become a vital aspect of cooperative ITS (C-ITS). With these emerging characteristics, the classical passing-through-intersection problem has gained new connotations, worth further exploring. After analyzing the essences of this new problem, service-oriented cooperation models and mechanisms for whole autonomous vehicles approaching intersections are investigated in this paper. First, related traffic objects and possible vehicular behaviors are abstracted and modeled with the cyber-physical cooperative features and QoS constraints. A new reservation-based scheduling procedure is then conducted by employing the concepts of vehicle-to-infrastructure communication, and typical vehicular passing-through behaviors and several spatial-temporal constraints are designed to coordinate vehicles passing through an intersection divided as a series of continuous static critical sections. Given these considerations, a priority-based centralized scheduling algorithm, named cs PriorFIFO, which adopts a novel priority inheritance mechanism to promote the traffic QoS of emergent vehicles, is proposed. Finally, all these designs are implemented in a traffic simulator named QoS-CITS, and the functions and the performance of these studied methods are verified and compared.

Adaptive green traffic signal controlling using vehicular communication

The importance of using adaptive traffic signal control for figuring out the unpredictable traffic congestion in today’s metropolitan life cannot be overemphasized. The vehicular ad hoc network (VANET), as an integral component of intelligent transportation systems (ITSs), is a new potent technology that has recently gained the attention of academics to replace traditional instruments for providing information for adaptive traffic signal controlling systems (TSCSs). Meanwhile, the suggestions of VANET-based TSCS approaches have some weaknesses: (1) imperfect compatibility of signal timing algorithms with the obtained VANET-based data types, and (2) inefficient process of gathering and transmitting vehicle density information from the perspective of network quality of service (QoS). This paper proposes an approach that reduces the aforementioned problems and improves the performance of TSCS by decreasing the vehicle waiting time, and subsequently their pollutant emissions at intersections. To achieve these goals, a combination of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications is used. The V2V communication scheme incorporates the procedure of density calculation of vehicles in clusters, and V2I communication is employed to transfer the computed density information and prioritized movements information to the road side traffic controller. The main traffic input for applying traffic assessment in this approach is the queue length of vehicle clusters at the intersections. The proposed approach is compared with one of the popular VANET-based related approaches called MC-DRIVE in addition to the traditional simple adaptive TSCS that uses the Webster method. The evaluation results show the superiority of the proposed approach based on both traffic and network QoS criteria.

Dynamic scheduling algorithm for LTE uplink with smart‐metering traffic

AbstractLong‐term evolution (LTE) is a promising last mile access candidate technology for the smart‐metering communication architecture. However, when the mobile LTE network is used to support smart meters (SMs), the quality‐of‐service (QoS) requirements of the smart‐metering traffic as well as all the other typical mobile network traffic need to be ensured. This becomes problematic when the network users generate diverse traffic types that have different QoS requirements. Therefore, in this paper, we propose a dynamic bandwidth scheduling algorithm to ensure the required QoS of various traffic types arising from both SMs and mobile users. Our proposed dynamic bandwidth allocation algorithm integrates two schedulers that are designed for periodic and emergency SM traffic situations that have different SM traffic intensities and QoS requirements. Designing of two schedulers provides the advantages of leveraging the particular traffic characteristics of these two diverse operational situations and achieving the maximum use of resources to ensure QoS requirements. In addition, to alleviate potential problems created by simultaneous emergency SM traffic, we also propose a method that deploys a random delay for SM packet transmissions. We analyse the delay and packet drop ratio of diverse traffic types when both the LTE base station scheduler and the SMs deploy our proposed methods under either periodic or emergency SM traffic conditions in the smart grid. Our results show that our proposed mechanisms are capable of satisfying the QoS requirements of both mobile users and SMs under diverse traffic conditions.

Dynamic slot-based carrier scheduling scheme for downlink multimedia traffic over LTE advanced networks with carrier aggregation

Carrier aggregation (CA) in long-term evolution advanced (LTE-A) networks is a promising tool for providing bandwidth extension for high data rate communication. In CA, the efficient scheduling of carriers has imposed a new challenge in the design of delay-sensitive carrier scheduling for mobile multimedia applications. In this paper, a new dynamic slot-based carrier scheduling scheme has been proposed for efficient resource allocation to support the quality of service (QoS) of mobile traffic over CA transmission. The key idea of this scheduling is the allocation of slots for each component carrier based on the queue state information, taking into consideration the priority based on the delay requirements of individual mobile multimedia traffic. Two different cases of the scheduler with and without priority are implemented to facilitate the performance comparison. The simulation results show that the proposed scheme provides better spectrum utilization, throughput, and delay performance than the existing scheduling scheme and improves delay-sensitive mobile traffic QoS.