Quality Of Service Classes Research Articles

Optimizing Capacity Assignment in Multiservice MPLS Networks

The general Multiprotocol Label Switch (MPLS) topology optimisation problem is complex and concerns the optimum selection of links, the assignment of capacities to these links and the routing requirements on these links. Ideally, all these are jointly optimised, leading to a minimum cost network which continually meets given objectives on network delay and throughput. In practice, these problems are often dealt with separately and a solution iterated. In this paper, we propose an algorithm that computes the shortest routes, assigns optimal flows to these routes and simultaneously determines optimal link capacities. We take into account the dynamic adaptation of optimal link capacities by considering the same Quality of Service (QoS) measure used in the flow assignment problem in combination with a blocking model for describing call admission controls (CAC) in multiservice broadband telecommunication networks. The main goal is to achieve statistical multiplexing advantages with multiple traffic and QoS classes of connections that share a common trunk present. We offer a mathematical programming model of the problem and proficient solutions which are founded on a Lagrangean relaxation of the problem. Experimental findings on 2-class and 6-class models are reported.

3GPP QoS-based scheduling framework for LTE

This paper proposes the design of a scheduling framework for the downlink of the Long Term Evolution (LTE) system with the objective of meeting the Quality of Service (QoS) requirements as defined by the QoS architecture of the 3G Partnership Project (3GPP) specifications. We carry out a thorough review of 3GPP specifications analyzing the requirements of the 3GPP QoS architecture. LTE bearers may be associated with a Guaranteed Bit Rate (i.e., GBR bearers) or not (i.e., non-GBR bearers). Additionally, the specifications establish a Packet Delay Budget (PDB) to limit the maximum packet transfer delay. To achieve our goal, we design a channel-aware service discipline for GBR bearers which is able to fulfill not only the GBR but also the PDB. Additionally, we also design an algorithm for prioritizing GBR and non-GBR bearers from different QoS Class Identifiers (QCIs) following 3GPP QoS rules. We compare the proposed framework with two reference schedulers by means of network-level simulations. The results will show the ability of the proposed framework to address the QoS requirements from 3GPP specifications while providing an interesting performance from a spectral efficiency viewpoint.

Efficient scheduling algorithm for multiple mobile subscriber stations with unsolicited grant service in an IEEE 802.16e network

The IEEE 802.16e standard introduces the concept of mobile subscriber stations (MSSs) to provide mobility support. Five quality of service (QoS) classes have been defined to meet the QoS requirement of different connections between a base station and a subscriber station. Among these QoS classes, unsolicited grant service (UGS) has been designed to support real-time service flows that periodically generate fixed-size data packets. Most of the existing scheduling schemes for a UGS class consider scheduling only a single MSS; even if such schemes consider multiple MSSs, the QoS requirement of such MSSs is not appropriately satisfied after scheduling. This paper proposes a scheduling scheme, which schedules multiple MSSs with UGS connections so that the QoS requirement of each MSS can be satisfied after scheduling. The simulation results showed that the proposed approach achieved a bandwidth utilization of more than 90% and did not incur a high bandwidth waste when the number of connections was high.

Improved MLWDF scheduler for LTE downlink transmission

ABSTRACTIn long-term evolution (LTE) downlink transmission, modified least weighted delay first (MLWDF) scheduler is a quality of service (QoS) aware scheduling scheme for real-time (RT) services. Nevertheless, MLWDF performs below optimal among the trade-off between strict delay and loss restraints of RT and non-RT traffic flows, respectively. This is further worsened with the implementation of hybrid automatic retransmission request (HARQ). As these restraints grow unabated with increasing number of user demands, the performance of MLWDF further reduces. In order to ameliorate this situation, there is a need to directly incorporate the variations in user demands and HARQ implementation as parameters to the MLWDF scheduler. In this work, an improvement to the MLWDF scheduler is proposed. The improvement entails adding two novel parameters that characterise user demand and HARQ implementation. The scheduler was tested using varying three classes of service in QoS class identifiers (QCIs) table standardised by Third Generation Partnership Project for LTE network to characterise different services. It was also tested on the basis of packet prioritisation. The proposed scheduler was simulated with LTE-SIM simulator and compared with the MLWDF and proportional fairness schedulers. In terms of delay, throughput and packet loss ratio; the proposed scheduler increased overall system performance.

A Dynamic Service Class Mapping Scheme for Different QoS Domains Using Flow Aggregation

This paper addresses the issue of provisioning end-to-end quality of service (QoS) for multimedia services over heterogeneous networks and introduces a parametric model by using network calculus theory for QoS class mapping between different QoS domains. Then, a QoS mapping scheme based on flow aggregation (QMS-FAG) is proposed in this paper to mitigate the information loss problem due to mapping between QoS domains with different granularity of QoS class and to provide efficient network resources utilization by considering user's quality of experience. In QMS-FAG, the QoS requirements of service flows are indicated by a unique FAG identifier, which is described in a service flow map of QoS parameters. With FAG identifier and mapping executors sitting at the border of different QoS domains, QMS-FAG allows smooth QoS class mapping between networks with different granularity of QoS class. Both numerical analysis and simulation studies are given to demonstrate the efficiency of the proposed method.

Service-differentiated downlink flow scheduling to support QoS in long term evolution

The growing demand of network services, especially for broadband downlink communication, has triggered the evolution of cellular systems. Recently, 3GPP continuously works out the standard of long term evolution (LTE) in response to the oncoming 4G cellular system. LTE adopts the OFDMA technology for downlink communication, and divides the spectral resource into physical resource blocks (PRBs). However, the LTE flow scheduling problem, which asks how to allocate PRBs to downlink flows for communication, is not well addressed in the standard but has great impact on transmission efficiency. On the other hand, LTE categorizes flows into guaranteed bit rate (GBR) and non-GBR classes, where GBR flows usually have higher priorities and shorter delay constraint than non-GBR flows. Although various solutions have been proposed to the LTE flow scheduling problem, many of them generally aim at maximizing transmission efficiency or keeping fair transmission, which may starve non-GBR flows or cannot well support quality of service (QoS) for GBR flows. Therefore, the paper develops a service-differentiated downlink flow scheduling (S-DFS) algorithm by taking the aforementioned difference between flows into consideration. Except for increasing transmission efficiency, S-DFS has two major goals: (1) satisfying the QoS requirement of GBR flows, and (2) ensuring the data transmission of non-GBR flows. Specifically, S-DFS first deals out PRBs to flows according to their channel conditions and QoS class identifier (QCI) defined in LTE. Then, with the mechanism of resource reallocation, S-DFS can assign a dynamic amount of reallocatable PRBs to the flows whose packets are about to be dropped. Experimental results demonstrate that S-DFS can achieve higher LTE transmission efficiency. Furthermore, it not only reduces both dropping ratio and delay of GBR packets, but also improves data throughput of non-GBR flows.

Co-channel Interference Avoidance Algorithm for Closed Access Femtocell Networks

ABSTRACTFemtocells play a promising role in next generation cellular networks as they provide high quality voice and data service to indoor users. However, deployment of dense, unplanned, and closed access femtocells over limited resource may induce co-tier co-channel interference (CTCCI) and cross-tier co-channel interference (XTCCI). These interferences seriously affect the quality of service (QoS) experienced by macro- and femtousers. To collectively handle such interferences, we propose an interference-free resource and power allocation (IFRPA) algorithm for macro-femtocell networks. Based on the channel quality indicator and out-of-boundary radiation, the IFRPA algorithm assigns downlink power and non-interfering downlink resource to the femtocells, thereby protecting the link quality of nearby co-channel deployed macro- and femtousers. Adopting frequency reuse phenomenon with centralized resource coordination has maximized resource utilization factor and overall service success ratio. Simulation results show that the IFRPA algorithm proposed by us makes the user to experience less XTCCI and CTCCI, which are below the tolerable limits, whereas the existing distributed random access (DRA) algorithm drowns the link quality of the users. Apart from interference reduction, QoS class identifier based service grant enables the IFRPA algorithm to offer significantly higher throughput and capacity compared with the DRA algorithm.

An analytic network process and trapezoidal interval‐valued fuzzy technique for order preference by similarity to ideal solution network access selection method

SummaryNext generation wireless networks consist of many heterogeneous access technologies that should support various service types with different quality of service (QoS) constraints, as well as user, requirements and provider policies. Therefore, the need for network selection mechanisms that consider multiple factors must be addressed. In this paper, a network selection method is proposed by applying the analytic network process to estimate the weights of the selection criteria, as well as a fuzzy version of technique for order preference by similarity to ideal solution to perform the ranking of network alternatives. The method is applied to a heterogeneous network environment providing different QoS classes and policy characteristics. Each user applies the method to select the most appropriate network, which satisfies his or her requirements in respect of his or her service‐level agreement (SLA). Performance evaluation shows that when the user requests only one service, the proposed method performs better compared to the original technique for order preference by similarity to ideal solution, as well as the Fuzzy AHP‐ELECTRE method. Moreover, the proposed method can be applied in cases where a user requires multiple services simultaneously on a device. The sensitivity analysis of the proposed method shows that it can be properly adjusted to conform to network environment changes. Copyright © 2014 John Wiley & Sons, Ltd.

A QoS control scheme using dynamic window size control for wide area ubiquitous wireless network

This paper describes a quality‐of‐service (QoS) control scheme for a wide‐area ubiquitous wireless network which is designed to accommodate many wireless terminals (WTs), such as sensors and actuators, in a large cell area. The purpose of this paper is to establish a QoS control scheme in a medium access control (MAC) layer that can hold the transmission delay of high‐priority class traffic within a predefined value regardless of how much low‐priority class traffic there is. Several QoS control schemes for wireless communication use have been proposed. However, in the wide‐area ubiquitous wireless network, an access point (AP) accommodates many WTs and the AP traffic volume often drastically changes. Therefore, conventional schemes sometimes cannot control the QoS of high‐priority traffic. To solve this problem, we propose a QoS control scheme that calculates a suitable initial back‐off window size of random access for each QoS class by using equations derived from a Markov chain behavior model. The proposed scheme adjusts the window size so as to prevent increased transmission delay of high‐priority traffic. The scheme's performance is clarified by computer simulation. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Intuitionistic Fuzzy Set Based Task Scheduling with QoS Preference Awareness

Existing task scheduling algorithms in cloud computing lack the ability to be aware of users' quality of service(QoS) preference. In order to address this problem, intuitionistic fuzzy analysis is introduced to determine users' QoS preference. In addition, the optimal sequence decision helps experts use their professional knowledge to decide the weights of QoS classes. Using these methods, we propose the Intuitionistic Fuzzy Set Based Task Scheduling with QoS Preference Awareness: IFS-QoS PA algorithm. By considering both user and expert experience, the method can determine users' QoS preference and reflect the characteristic of cloud storage system. The simulation results show that this method offers acceptable user satisfaction rate, has low computation complexity and more suitable for large scale task scheduling as compare to particle swarm optimization based ones.

Maximization of the Supportable Number of Sensors in QoS-Aware Cluster-Based Underwater Acoustic Sensor Networks

This paper proposes a practical low-complexity MAC (medium access control) scheme for quality of service (QoS)-aware and cluster-based underwater acoustic sensor networks (UASN), in which the provision of differentiated QoS is required. In such a network, underwater sensors (U-sensor) in a cluster are divided into several classes, each of which has a different QoS requirement. The major problem considered in this paper is the maximization of the number of nodes that a cluster can accommodate while still providing the required QoS for each class in terms of the PDR (packet delivery ratio). In order to address the problem, we first estimate the packet delivery probability (PDP) and use it to formulate an optimization problem to determine the optimal value of the maximum packet retransmissions for each QoS class. The custom greedy and interior-point algorithms are used to find the optimal solutions, which are verified by extensive simulations. The simulation results show that, by solving the proposed optimization problem, the supportable number of underwater sensor nodes can be maximized while satisfying the QoS requirements for each class.

A Fair and QoS-Aware Resource Allocation Scheme in UWB WPANs with WiMedia Distributed MAC

Merits of distributed medium access control specified by WiMedia Alliance such as distributed nature and high data rate make it a favorite candidate standard for high rate wireless personal area network. However, the current WiMedia MAC standard has not considered supporting Quality of Service (QoS) even though QoS parameters such as a range of service rates are provided to each traffic stream (TS). Therefore, we propose a fair and QoS-aware resource allocation method that provides a fair and maximized QoS for all TSs according to the current traffic load condition and differentiates SoQ among different QoS classes while guaranteeing fairness of SoQ within a QoS class in a fully distributed manner. Even in case that the traffic load varies, each device independently recognizes the changes and calculates fair and maximum allowable service rates for TSs. From the simulation results, it is proven that the proposed method achieves high capacity of TSs and fair QoS provisioning under various traffic load conditions.

A Multi-link Mechanism for Heterogeneous Radio Networks

Nowadays, smart mobile devices drive the mobile traffic growth rapidly. Most smart mobile devices are equipped with multiple radio network interfaces, such as High Speed Packet Access (HSPA), Long Term Evolution (LTE), and Wi-Fi. Therefore, integration of multiple networks is a viable solution to fulfill traffic offloading and the Quality-of-Service (QoS) requirement of data usage for mobile users. In this paper, we propose a multi-link mechanism to handle the radio network selection and switching between LTE and Wi-Fi networks. A Multi-Link Adaptor (MLA) and a Multi-Connection Manager (MCM) are proposed for the User Equipment (UE) and the core network, respectively, to handle the multi-link mechanism. The applications executed in the UEs do not need to be modified under the proposed approach. The MLA maintains a QoS class table and a routing table for the network selection procedure and uses the GPRS Tunneling Protocol-Control plane (GTP-C) control messages to execute network switching. In the future, we will measure the throughput of the multi-link network and the switch delay between the heterogeneous radio networks.

Bounds and Constructions for Two‐Dimensional Variable‐Weight Optical Orthogonal Codes

AbstractOptical orthogonal codes (1D constant‐weight OOCs or 1D CWOOCs) were first introduced by Salehi as signature sequences to facilitate multiple access in optical fibre networks. In fiber optic communications, a principal drawback of 1D CWOOCs is that large bandwidth expansion is required if a big number of codewords is needed. To overcome this problem, a two‐dimensional (2D) (constant‐weight) coding was introduced. Many optimal 2D CWOOCs were obtained recently. A 2D CWOOC can only support a single QoS (quality of service) class. A 2D variable‐weight OOC (2D VWOOC) was introduced to meet multiple QoS requirements. A 2D VWOOC is a set of 0, 1 matrices with variable weight, good auto, and cross‐correlations. Little is known on the construction of optimal 2D VWOOCs. In this paper, new upper bound on the size of a 2D VWOOC is obtained, and several new infinite classes of optimal 2D VWOOCs are obtained.

Joint Load Balancing of Radio and Transport Networks in the LTE Systems

Load Balancing (LB) is an important mechanism often used in the cellular networks to offload the excessive traffic from high-load cells (hot spots) to low-load cells. Extensive studies have shown that the system level performance with LB can be greatly enhanced in terms of e.g. higher overall system throughput, lower user blocking ratio and better QoS (Quality of Service) for the users at the cell boundaries. However, so far the conventional LB solutions are mainly focusing on Radio Networks (RN), and little consideration of the impact from Transport Networks (TN) has been taken into account in the LB mechanisms. This paper proposes a joint load balancing framework for the Long Term Evolution system. The proposed LB takes into consideration the joint impact of RN and TN by combining the network-wide utilities to achieve overall network optimizations. In this paper, we suggest different utilities for GBR and nGBR service categories. For each service category, the proposed utilities consider multiple QoS classes with different services (e.g. VoIP, video and FTP) and aim to guarantee their individual QoS requirements. The presented numeric results show that the proposed mechanism can outperform the conventional RN-only LB, especially for the situation that the TN last mile link is the bottleneck and its deploy-ment is heterogeneous.

A Traffic Classification Agent for Virtual Networks Based on QoS Classes

Internet growth drives the emergence and usage of new applications, which have specific requirements for Quality of Service (QoS). Thus, differentiation of packets which belong to certain QoS classes becomes a crucial factor to ensure the desirable quality for the applications. Within this context, this paper proposes an agent for real-time traffic classification based on QoS classes for virtual network environments, which aims at forwarding the flow to the adequate virtual network according to the QoS class. The study was made using the Mininet emulator and the Openflow Protocol. And the study showed that the agent using the Naive Bayes method performs the more suitable classification in real time.

DDP: A Dynamic Dimensioning and Partitioning model of Virtual Private Networks resources

In this paper, we consider the problem of optimizing the Virtual Private Network Provider’s (VPNP) profit by providing a periodic Dynamic Dimensioning and Partitioning (DDP) model for utilizing network resources. In literature, Complete Sharing (CS), Complete Partitioning (CP), and Bandwidth Borrowing (BR) techniques have been proposed for resource allocation where the following limitations can be noticed: VPN operators can exaggerate their needs for resources so the resources might be underutilized and optimal bandwidth utilization is not guaranteed. Moreover, all the aforementioned techniques use a static dimensioning of network resources. Hence, it may result in a high blocking of VPN connections and resource underutilization resulting in reduced profit. To overcome the above limitations, we propose to dynamically partition the resources over different QoS classes and dynamically dimension the capacity of the required links. The DDP model will run periodically through auctions that can reduce the reasoning of exaggeration and maximize VPNP’s profit. Moreover, our solution guarantees the reservation of the previously allocated resources for the coming auction periods. Thus, we formulate our problem as Mixed-Integer Linear Program (MILP) that allows us to: (i) minimize the network dimensioning cost, (ii) maximize the VPNP profit through the Profit Percentage Parameter (PPP), (iii) provide the optimal bandwidth division of each network link among Quality of Service (QoS) classes, and (iv) calculate the optimal routing of new VPN connections without disruption of the demands accepted in previous periods. To reduce the impact of resources’ reservation, we propose a pricing approach based on Vickrey–Clarke–Groves (VCG) mechanism that is able to reduce: (i) the risk of profit loss due to reservation, and (ii) the risk of having unutilized resources.

Analysis Framework for Opportunistic Spectrum OFDMA and Its Application to the IEEE 802.22 Standard

We present an analytical model that enables throughput evaluation of Opportunistic Spectrum Orthogonal Frequency Division Multiple Access (OS-OFDMA) networks. The core feature of the model, based on a discrete time Markov chain, is the consideration of different channel and subchannel allocation strategies under different Primary and Secondary user types, traffic and priority levels. The analytical model also assesses the impact of different spectrum sensing strategies on the throughput of OS-OFDMA network. The analysis applies to the IEEE 802.22 standard, to evaluate the impact of two-stage spectrum sensing strategy and varying temporal activity of wireless microphones on the IEEE 802.22 throughput. Our study suggests that OS-OFDMA with subchannel notching and channel bonding could provide almost ten times higher throughput compared with the design without those options, when the activity and density of wireless microphones is very high. Furthermore, we confirm that OS-OFDMA implementation without subchannel notching, used in the IEEE 802.22, is able to support real-time and non-real-time quality of service classes, provided that wireless microphones temporal activity is moderate (with approximately one wireless microphone per 3,000 inhabitants with light urban population density and short duty cycles). Finally, two-stage spectrum sensing option improves OS-OFDMA throughput, provided that the length of spectrum sensing at every stage is optimized using our model.

Resource Allocation with Interference Avoidance in OFDMA Femtocell Networks

Interference control and quality-of-service (QoS) awareness are the major challenges for resource management in orthogonal frequency-division multiple access femtocell networks. This paper investigates a self-organization strategy for physical resource block (PRB) allocation with QoS constraints to avoid the co-channel and co-tiered interference. Femtocell self-organization including self-configuration and self-optimization is proposed to manage the large femtocell networks. We formulate the optimization problem for PRB assignments where multiple QoS classes for different services can be supported, and interference between femtocells can be completely avoided. The proposed formulation pursues the maximization of PRB efficiency. A greedy algorithm is developed to solve the resource allocation formulation. In the simulations, the proposed approach is observed to increase the system throughput by over 13% without femtocell interference. Simulations also demonstrate that the rejection ratios of all QoS classes are low and mostly below 10%. Moreover, the proposed approach improves the PRB efficiency by over 82% in low-loading scenario and 13% in high-loading scenario.

Modeling and performance analysis of uplink scheduling algorithm in mobile WiMAX systems

Extensive numbers of the IEEE 802.16e Mobile WiMAX scheduling proposals focus on simulation for obtaining performance measures of the proposed scheduling algorithm. There is also handful of article that focused on the mathematical modeling. However, the model is derived assuming the traffic from different quality of service (QoS) classes is separated, which allow for independent analysis. In this paper, we propose an uplink (UL) scheduling algorithm that considers the adaptive modulation and coding scheme and QoS parameters of all five service classes. The resources are distributed in two stages. The first stage allocates the resources to different classes of service in accordance to the threshold based priority while the second stage allocates the resources within the same class with the exhaustive service strategy. A mathematical model that combine the different QoS classes of Mobile WiMAX is formulated and it is derived based on the weighted sum of the mean waiting time for the individual queues or known as pseudo-conservation law.