QoS Provisioning Research Articles

Cross-Layer Optimization for Statistical QoS Provision in C-RAN With Finite-Length Coding

Cross-Layer Optimization for Statistical QoS Provision in C-RAN With Finite-Length Coding

QoS Provision for Industrial IoT Networking: Multiantenna NOMA Based on Partial CSIT

QoS Provision for Industrial IoT Networking: Multiantenna NOMA Based on Partial CSIT

Multi-Objective Multi-Dimensional Resource Allocation for Categorized QoS Provisioning in Beyond 5G and 6G Radio Access Networks

Multi-Objective Multi-Dimensional Resource Allocation for Categorized QoS Provisioning in Beyond 5G and 6G Radio Access Networks

Packet Scheduling in Multi-Flow Carrier Aggregation with QoS Provisioning: Cross-Layer Design and Performance Analysis

Packet Scheduling in Multi-Flow Carrier Aggregation with QoS Provisioning: Cross-Layer Design and Performance Analysis

Improve the quality of service through secure routing networks secured in the mail

A mobile ad hoc network (MANET) is a stand-alone system with mobile nodes. Nodes can move around at will. Communication is subject to security breaches without a centralized, secure infrastructure, and the nodes are the biggest offenders. Since security has become one of the most important issues for data transfer via wired and wireless networks, many security-enhanced solutions have been created to enhance the security of data transmission over public networks. The goal of this project is to make routing safer. Proactive routing, as is well known, involves finding alternative routes and requiring packets to choose one at random from their immediate neighbors. Sending hello packets allows us to maintain track of each node's neighbors. The delivery path is then selected from nearby nodes, with the prior hop which is retained as the history node having been arbitrarily excluded. To randomize delivery channels, the proactive routing protocols DSDV and RDSDV were contrasted for various node counts. The Simulation employs this project. The rapid development of mobile computing appli-cations and distant systems has raised awareness of quality of service (QoS) for mobile ad hoc networks (MANETs). In the MANET sce-nario, security is a key component of Qos provisioning. Attacks on the system could result in problems with direction, asset reservations, or even the collapse of the QoS structure if no security tool is used. In this study, two new plans will be provided from the perspectives of two alternative techniques to manage the updating of the organizational idea and allay the worries caused by interface annoyances in order to handle the security challenges of MANET Qos and the actual commitments of this investigation.

Performance study of visible light communication through non-orthogonal multiple access (noma) – LI-FI

Li-Fi (Light Fidelity) is a new wireless communication technology that is comparable to Wireless Fidelity (Wi-Fi). However, Li-Fi is supposed to be better than Wi-Fi, and this has been theoretically verified. Li-Fi is also thought to make a significant contribution to wireless networks. The practical application of Li-Fi will be discussed in this study. In this paper we chose NOMA because of its ability and efficiency in simultaneously transporting data, as well as its application in 5G cellular networks. VLC stands for visible light communication, as the name implies. In this section, we will investigate how the data transporting capabilities of Li-Fi make use of the visible light emitted by light emitting diodes (LEDs). In this paper, the effectiveness of a non-orthogonal multiple access (NOMA) protocol used in a downlink visible light communication (VLC) system is evaluated for two distinct situations. On a two-user paired NOMA, we create an analytical expression of the system coverage probability for QoS provisioning and show that optimum power allocation coefficients do exist. Additionally, we establish the existence of optimal power allocation coefficients. Last but not least, the numerical and analytical results illustrated in our work show that the VLC single-cell system throughput obtained with our technique is better than that obtained with the earlier strategy. Additionally, it is shown that the suggested alternative lower bound fits the original NOMA-VLC GRPA objective asymptotically using indoor VLC channels.

Hybrid Learning based Radio Resource Management in 5G Heterogeneous Networks

Ultradensification using different types of small cells (SCs) is one of the key enabling solutions to meet the multiple stringent requirements of 5G cellular networks. However, radio resource management (RRM) in ultra-dense heterogeneous networks (HetNets) is not easy due to interferences in multi-tiered architecture and dynamic network conditions. Interferences in 5G HetNets can be efficiently managed only through the techniques which are adaptive and self-organizing to handle dynamic conditions in 5G HetNets. In this article, a machine learning (ML) based self-adaptive resource allocation scheme is proposed based on the combination of independent and cooperative learning and evaluated for ultra-dense 5G HetNets. The proposed scheme aims to improve the QoS of all users associated with different network tiers in ultra-dense HetNets simultaneously. The proposed solution adaptively optimizes the SCs transmit power either through independent learning or cooperative learning based on the varying density of small cells to minimize the interferences and ensure minimum QoS requirements for all users in different network tiers. The proposed scheme not only maintains the minimum required capacities for QoS provision to all users simultaneously but has also shown a significant improvement in the capacities of users in different network tiers in high interference scenarios as compared to the use of a single learning scheme.

Slow and fast adaptive modulation and coding for uplink massive MIMO systems with packet retransmission

Here, the authors consider the uplink of a cellular massive multiple-input multiple-output (MIMO) system with maximum ratio combiner (MRC) at base stations (BSs). To achieve a better QoS provisioning, users in the cells employ link adaptation using adaptive modulation and coding (AMC) in conjunction with packet retransmission. The authors present a cross-layer approach for the AMC design exploiting the time variation feature of MIMO wireless channels. At first, a fast AMC (FAMC) scheme is proposed to adapt the fast small-scale fading of the wireless channel based on the instantaneous channel state information. Since the fast fading is asymptotically averaged out due to the channel hardening property of massive MIMO system, we then suggest a slow AMC (SAMC) scheme which adjusts the adaptation parameters based on only the large-scale channel fading statistics including shadow fading and pass loss of the channel. The SAMC substantially reduces the feedback rate and implementation cost because of using a larger coherence time compared to that of the FAMC. For the proposed schemes, the probability density function of signal-to-interference-plus-noise ratio (SINR) for MRC receivers at BSs is analytically derived and verified by simulation. Also, closed-form expressions are presented for the throughput and packet error outage of the system. Index Terms—Massive MIMO, MRC, AMC, ARQ, Performance analysis.

Design, modeling and optimization using hybrid virtual topology for QoS provision over all-optical switched networks

All-optical switched networks (AOSN), mainly optical label switching (OLS), guaranteed fast data transfer QoS support and network resource supervision. However, the emergence of new applications and services, having variable and various requirements, are produced new demands, notably in terms of QoS support and resource control. To meet these demands, a hybrid virtual topology (HVT), with multiple core node architectures employing wavelength converters (WC), fiber delay line (FDL), and deflection path (DP), is proposed. This HVT enables various node architectures to manage the availability and usage of the components, covering fixed, limited, and full range converters (FXWC, LRWC, and FRWC) also FDL. An advanced DP improves signaling and switching to supervise the potential HVT and AOSN resources while assuring QoS support. A lightpath cost is formulated to determine the potential lightpaths utilized to build the HVT guaranteeing AOSN resources and advanced traffic management. The obtained results of the conducted simulation and comparative study show that the optimized (O-HVT) approach performed better than the enhanced (E-HVT) and initial (I-HVT) approaches. Moreover, the O-HVT method optimizes AOSN resources, mainly core node architecture range, while providing QoS support for high load traffic with variable demands.

QoS provision for vehicle big data by parallel transmission based on heterogeneous network characteristics prediction

Multipath parallel transmission has become an important research direction to improve big data transmission efficiency of connected vehicles. However, due to the heterogeneity and time-varying characteristics of parallel transmission paths, packets transmitted in parallel are usually out-of-order delivered to the destination, which greatly limits the throughput. To Lift the restriction of out-of-order delivery on the efficiency of big data transmission, this paper proposes a packet-granular real-time shortest delay scheduling scheme for multipath transmission based on path characteristics prediction. The scheme first clusters and models the heterogeneous network, which greatly reduces the complexity of the network. Subsequently, a prediction algorithm that can quickly converge to real-time delay is proposed. Then the details of the scheduling scheme are introduced by modules, and the bandwidth aggregation efficiency close to the theoretical upper limit is proved through simulation. Finally, we summarize the applicable scenarios and future work of the scheme.

Joint Provisioning of QoS and Security in IoD Networks: Classical Optimization Meets AI

The emerging unmanned aerial vehicle (UAV)-based communication networks, with the tight integration of the Internet of Things (IoT), are rapidly gaining prominence as the emerging Internet of Drones (IoD) paradigm. While IoD appears as an agile network to serve both mobile users and massive machine-to-machine communication and IoT traffic, it confronts sharply increasing security and privacy concerns due to the exponentially rising “untrusted” links and zero-day attacks in 5G and beyond networks. While security provisioning is important, its strict enforcement is known to significantly impact the service quality of the users. In this article, by discussing the tradeoff between tightly coupled provisioning of the quality of service and security performance of users, we first formulate an optimization problem to maximize the security levels subject to constraints specific to the considered IoD system. Then we demonstrate that the formulated problem is computationally hard. We describe existing methodologies that may be readily applicable to solve the problem, which may, however, not yield any solution even if a solution exists. To address this problem, we propose a simple but effective adaptive boosting-based method to maximize the security levels without significantly sacrificing network performance. The effectiveness of our proposed method is demonstrated and compared with existing methods using computer-based simulations.

QoS Provisioning in Wireless Mesh Networks: A Survey

QoS Provisioning in Wireless Mesh Networks: A Survey

An Enhanced Framework for Traffic Load Balancing and QoS Provisioning in SDN

An Enhanced Framework for Traffic Load Balancing and QoS Provisioning in SDN

Swarm intelligence inspired meta-heuristics for solving multi-constraint QoS path problem in vehicular ad hoc networks

Applications and services which run on top of vehicular ad hoc networks range from human safety and traffic management to assisted driving and real time battlefield communication. Many of these applications may have low-elasticity QoS requirements. Characteristics like high mobility of vehicles, dynamic topology, inherent distributed nature and consequent lack of central coordination make it challenging to provide QoS support in such networks. Since, QoS provisioning and path finding can be potentially handled together, this work aims at exploiting such a possibility. Consequently, an attempt has been made to solve the multi-constraint QoS optimal path problem by using an innovative combination of swarm intelligence based optimization strategies and an especially designed cost function. This work also presents a detailed theoretical as well as experimental analysis of the proposed algorithms, probably first of its kind. Additionally, the analysis part also investigates the applicability issues and related solutions considering select algorithms in view of solving the given problem for vehicular ad hoc networks. Meta-heuristics derived in this process have been applied on realistic modelled vehicular ad hoc network topology and as the presented analysis would indicate results are encouraging.

Impact of Intermediate Bottleneck Nodes on the QoS Provision in Wireless Infrastructure less Networks

Wireless Infrastructure less networks consist of wireless mobile nodes with heterogeneous and constrained resources, to establish internet connectivity regardless of the location. The applications the networks are disaster relief, health care and military. These applications are sensitive, and demands the reliable, and best quality of communication. Routing is one of the resources to enable the communication. Routing is acceptable in an infrastructure less networks if it satisfies the quality of service requirements. Thus the paper aims to investigate the existing QoS routing protocol performance in various conditions. The aim is to achieve a broad understanding of QoS routing protocol designed for Wireless Infrastructure less networks, and further pave the pathway for future research. The paper analyses the QoS routing protocol performance in presence of bottleneck intermediate node, and it is the novel aspect of the work.

An End-to-End (E2E) Network Slicing Framework for 5G Vehicular Ad-Hoc Networks

Network slicing is emerging as a promising solution for end-to-end resource management and orchestration together with Software Defined Networking (SDN) and Network Function Virtualization (NFV) technologies. In this paper, a comprehensive network slicing framework is presented to achieve end-to-end (E2E) QoS provisioning among customized services in 5G-driven VANETs. The proposed scheme manages the cooperation of both RAN and Core Network (CN), using SDN, NFV and Edge Computing technologies. Furthermore, a dynamic radio resource slice optimization scheme is formulated mathematically, that handles a mixture of mission-critical and best effort traffic, by delivering the QoS provisioning of Ultra-reliability and low latency. The proposed scheme adjusts the optimal bandwidth slicing and dynamically adapts to instantaneous network load conditions in a way that a targeted performance is guaranteed. The problem is solved using a Genetic Algorithm (GA) and results are compared with the previously proposed 5 G VANET architecture. Simulation reveal that the proposed slicing framework is able to optimize resources and deliver on the key performance metrics for mission critical communication.

WITHDRAWN: Implementation of QOS metrics in Multi-hop cognitive radio routing protocol in heterogeneous environment

Abstract With the benefit of have privileged spectrum utilization efficiency, this network are quickly adapt for the provisioning of high qos contribution within wireless network. The cognitive based network, has specified a higher opportunity of receiving huge throughput giving a provision of high qos provisioning for the subsequently generation upcoming services In addition, the routing metrics use in multi-hop CRMANETs be supposed to reproduce the band ease of use, the links eminence, The PU behavior and quality of service (Qos) Necessities of secondary users. In favor of the most excellent of awareness, numerous of researchers investigate the presentation of the diverse routing protocols in a homogeneous surroundings only. In this article, we suggest a heterogeneous cognitive radio routing protocol (HCR) Ope Rates In Heterogeneous Environment (Organized Into Hierarchical Clusters). The projected routing protocol is suspiciously developed to formulate a substitution linking the channel diversity of the routing path next to with the CRMANETs throughput. With simulation, we talk about the performance of the future HCR routing protocol and evaluate it with the AODV routing protocol by means of a MATLAB simulation.

Self-attentive deep learning method for online traffic classification and its interpretability

Traffic classification is one of the fundamental tasks in computer networking. This task aims to associate network traffic to a specific class according to the requirements (e.g., QoS provisioning). Online classification, which refers to the situations where flows need to be classified in real time, is an essential technique for this topic. In recent academic research, traffic classification methods based on machine learning (ML) or deep learning (DL) have been proposed. However, most of these methods take flow-level data as input, which requires observing the entire or large portion of a flow and violates the restrictions of online classification. Furthermore, the DL-based methods scarcely discuss the interpretability (e.g., which features are learned by DL, where is the discrimination power from). The lack of interpretability makes people question their reliability and may hinder their further applications. In this paper, we propose a self-attentive method (SAM) for traffic classification. We properly design a neural network whose input can be more fine-grained (i.e., packet-level). This neural network outputs classification results (∼2ms per packet) and consequently satisfies the requirements of online classification. Furthermore, a new technique called self-attention mechanism is utilized for interpretability exploration. By assigning attentive weights to different parts of the input, the self-attention mechanism allows us to understand how the DL model learns discriminative features from the input. According to experimental results, SAM outperforms the current state-of-the-art schemes, improving classification accuracy by ∼8% (protocol classification), ∼5% (application classification), and ∼13% (traffic type classification). The code is available at https://github.com/xgr19/SAM-for-Traffic-Classification.

Toward 5G High Utilizations: A survey on OFDMA-based Resource Allocation Techniques in Next-Generation Broadband Wireless Access Networks

LTE is marketed as 4G standard for wireless communication services. LTE network technologies provide a high speed triple play services like data, voice, and video with QoS provision. The resource allocation techniques primary concerns are the QoS support that aims to sat

GlobeSnap: An Efficient Globally Consistent Statistics Collection for Software-Defined Networks

Software defined networking (SDN) controller requires crucial statistics like flow-wise statistics from the switches to make decisions related to routing, load balancing, and QoS provisioning. These statistics, when viewed across the switches are likely to be inconsistent if a specific order is not enforced while collecting statistics. Collecting consistent statistics requires coordination among all the participating switches. A few approaches in the literature collect globally consistent statistics of a network in the SDN domain. However, these approaches are not time-efficient, robust, and synchronous for OpenFlow based networks. We propose, GlobeSnap, a time-efficient, robust, and synchronous method to collect globally consistent statistics for OpenFlow networks. GlobeSnap collects consistent statistics for all flows in a single round and is therefore, time-efficient. Moreover, GlobeSnap is robust since it resumes the statistics collection process from where it left in case of interruption. GlobeSnap also provides a near-synchronous snapshot of statistics of the switches traversed by a given flow. We also propose a mechanism to persistently store states in OpenFlow based networks using registers, multiple flow tables, and multiple pipelines. We find that GlobeSnap outperforms the state-of-the-art approaches in consistency evaluation. Further we present two use-cases which are sensitive to inconsistent flow statistics, that is, computing packet loss and identifying bottleneck links, to show the time-efficiency, robustness, and synchronicity of GlobeSnap. GlobeSnap provides 100% consistency in OpenFlow based SDN networks. Whereas the existing methods achieve a maximum of 59.89% consistency.