QoS Control Research Articles

Design of Real-Time Streaming Media Distribution MStreaming System

This article taking into account the network efficiency, QoS, resource consumption, latency, performance and ease of use, and implementation of the system on the basis of factors such as the complexity, media management, node in the system management, and streaming media QoS control, buffer management, incentives, and other key algorithm and protocol analysis and design, and trying to achieve a balance between the factors. Finally developed real-time streaming data distribution system based on P2P MStreaming program, its resources quickly and easily launch and positioning, exert the advantage of P2P technology can effectively solve the problem of server bottleneck link, decentralized services and resource consumption.

Study on Streaming Media Tentative Rate Control Algorithm Based on TCP-Friendly

In TCP-IP network environment that can’t provide a reliable guarantee of QoS, congestion and insufficient bandwidth becoming a major bottleneck in network applications, in order to prevent multimedia streaming occupied too many network resources ,leading to the traditional TCP flow can’t be normal transmission, the paper analyzes the RTP protocol QoS control and TCP congestion control mechanism ,directs the phenomenon of multimedia streaming flow seizing the traditional network resources, and proposes a tentative for streaming media rate control algorithm, effectively ensuring the multimedia streaming and traditional TCP flows to friendly coexist and fair competition.

Impact and control of network QoS on smart grid controlled electrical vehicle charging

Novel, networked information-rich control systems are emerging to provide a stable and cost-efficient operation of future electricity distribution grids. However, the dependence on fault-prone, low-cost, and heterogeneous network technologies and architectures challenges the grid control quality. In this work, we study the impact of varying network QoS for M2M connectivity on the low voltage grid operation in an electrical vehicle charging scenario. The analyzed charging control system relies on: (a) grid power sensing using smart meters via high latency power line communication and, (b) charging point actuation commands disseminated via unreliable wireless links (IEEE 802.11). Based on emulation results, we quantify the maximum acceptable meter reading delay from network transmission that sufficiently minimizes load prediction error. Further, based on the introduction of a timed reliable communication protocol, it is shown how changing the trade-off in QoS parameters of delay, loss and information inconsistency can be applied to overcome degradation of controller performance.

Enhanced quality of service control scheme with high availability for self-optimising wireless sensor network

Whereas various aspects in wireless sensor networks WSNs have been extensively investigated, the quality of service QoS control remains relatively unexplored. QoS is defined as the number of awakened sensors in a WSN. Sensor deaths caused by running out of battery and sensor replenishments caused by redeployment of new sensors contribute to the difficulty in controlling QoS in WSNs. A previous study developed a QoS control scheme based on the Gur Game paradigm. The Gur Game-based scheme can effectively adjust active sensors to a desired QoS without the information of total sensor numbers. However, this approach is only applicable to a range of desired QoS. This limitation decreases the availability and the application of the Gur Game-based scheme. The present study proposes an enhanced QoS control scheme, namely, the high-availability QoS control HAQC, which increases the availability range by applying a divide-and-conquer concept. The present study also uses the distribution used in the previous study. Simulations that compared our technique with those applied in other studies in various environments demonstrate that our scheme ensures a robust and high-availability sensor network capable of dynamically adjusting active sensors.

Towards voice/video application support in 802.11e WLANs: A model-based admission control algorithm

Supporting emergent voice/video applications in all wireless technologies is a requirement in the Next Generation Network (NGN) where Wireless Local Area Networks (WLANs) is a main component. For this type of applications, QoS needs to be fully maintained in order to assure user satisfaction. Actually, QoS control in 802.11e WLANs to support real time voice/video services remains an open problem. All the solutions that only aim to enhance the performance of the Enhanced Distributed Channel Access (EDCA) mechanism cannot resolve the performance degradation problem once the channel becomes saturated. Hence, an efficient admission control scheme in EDCA is the key to guarantee the QoS required by voice/video services in WLANs. In this paper, we propose a model-based admission control algorithm that is located within the QoS Access Point (QAP). An accurate analytical model is used to predict the QoS metrics that can be achieved once a new flow is introduced in the WLAN. Based on this prediction and on the QoS constraints of already admitted (active) flows as well as of the new flow, the QAP takes the appropriate decision for the new flow. The proposed admission control scheme is fully compatible with the legacy 802.11e EDCA MAC protocol. It is validated numerically and through simulations using several realistic usage scenarios.

Bubble-flux

Ensuring the quality of service (QoS) for latency-sensitive applications while allowing co-locations of multiple applications on servers is critical for improving server utilization and reducing cost in modern warehouse-scale computers (WSCs). Recent work relies on static profiling to precisely predict the QoS degradation that results from performance interference among co-running applications to increase the number of "safe" co-locations. However, these static profiling techniques have several critical limitations: 1) a priori knowledge of all workloads is required for profiling, 2) it is difficult for the prediction to capture or adapt to phase or load changes of applications, and 3) the prediction technique is limited to only two co-running applications. To address all of these limitations, we present Bubble-Flux , an integrated dynamic interference measurement and online QoS management mechanism to provide accurate QoS control and maximize server utilization. Bubble-Flux uses a Dynamic Bubble to probe servers in real time to measure the instantaneous pressure on the shared hardware resources and precisely predict how the QoS of a latency-sensitive job will be affected by potential co-runners. Once "safe" batch jobs are selected and mapped to a server, Bubble-Flux uses an Online Flux Engine to continuously monitor the QoS of the latency-sensitive application and control the execution of batch jobs to adapt to dynamic input, phase, and load changes to deliver satisfactory QoS. Batch applications remain in a state of flux throughout execution. Our results show that the utilization improvement achieved by Bubble-Flux is up to 2.2x better than the prior static approach.

Survey on application-layer mechanisms for speech quality adaptation in VoIP

VoIP calls are sensitive to several impairments, such as delay and packet loss. One way to overcome these problems is by adaptively adjusting application-layer parameters to keep a minimum speech quality level. At the heart of self-adaptive systems lies a feedback loop , which consists of four key activities: monitoring, analysis, planning, and execution. Nevertheless, the existing adaptive approaches to QoS control of VoIP do not explicitly exhibit this feedback loop. Bringing it to surface can help developers in designing more robust and human-independent VoIP systems. This survey presents a comprehensive review of the current state-of-the-art research on speech quality adaptation of VoIP systems at the application layer and some research challenges on this subject.

QC2: A QoS Control Scheme with Quick Convergence in Wireless Sensor Networks

In wireless sensor networks, too many or too few power-on sensors may cause the waste of resources or poor sensing efficiency; thus, controlling the number of active sensors to meet the predicted target number is the purpose of this research. However, the total number of sensors may be unstable because of the increment and damage to the sensors. It is difficult to control the number of active sensors to meet the predicted target in this condition. Previous studies proposed the Gur Game algorithm to solve this problem. However, the convergence time of the Gur Game algorithm is too long, which causes sensors to consume excessive power and waste resources. Therefore, this paper proposed the QoS Control with Quick Convergence (QC2). This method utilizes total virtual value to accelerate the convergence operation from the number of sensors to the target number. The experiment result shows that the QC2 method can cause the number of sensors to converge rapidly with the target value and that QC2 can be over a hundred times faster than the Gur Game algorithm with regard to convergence.

QoS Control and QoE Assessment in Multi-Sensory Communications with Haptics

QoS Control and QoE Assessment in Multi-Sensory Communications with Haptics

QoS Control Method Based on Adaptive Cooperation between Network Coding and IEEE 802.11e EDCA

QoS Control Method Based on Adaptive Cooperation between Network Coding and IEEE 802.11e EDCA

User-Oriented QoS Control Method Based on CSMA/CA for IEEE802.11 Wireless LAN System

User-Oriented QoS Control Method Based on CSMA/CA for IEEE802.11 Wireless LAN System

Method for Collecting Context Information in Mobile Communication Networks

This study proposesa system structure for the effective control of an external profilecreated from each heterogeneous network and an internal profile created from each task’s performance. It also provides an independent system operation algorithm and high-speed handshaking methodby excluding the disorderly connection between system operating algorithms (e.g. handover, resource allotment, QoS control), the related cells, and complex conformityand bystoring information on theproposedmonitoring system context and processing structure. Monitoring dynamically controls the related function setting according to changesin thecontext information of the mobile handset and station, and each function interacts as each function adjusts to change and is controlled and reorganized.

Deterministic Bounds on Performance of Self-Similar Network Based on ETS

According to the traffic regulating method and the traffic scheduling method of QoS control methods, this paper regulates traffic using the fractal regulator and proposes the arrival curve according to the output envelope of the fractal regulator. In addition, we put forward the service curve based on Enhanced Transmission Selection (ETS). Finally, we drive the deterministic bounds on performance of the self-similar network using the arrival curve and the service curve based on network calculus. These bounds have reference value for QoS guarantee, admission control and network planning.

Maritime Wireless Data Communications of Predictive Frequency Hopping Technique

In this paper, For 4th generation wireless communication systems, we propose a method to predict FH patterns in FH-OFDMA systems. OFDM is recognized as a promising modulation technique. Multi-user allocation in OFDM system can use FH that provides the spectrum-spread techniques. If one can generate more predictable FH sequences, then performance of the system can be easily improved. Current random FH and simple adaptive FH methods, however, are not considering predicting FH sequences. In this paper we show that the sampling of the wireless faded signal is not realized as a certain probability nature. With this regard, the proposed predictive FH allocation method is designed to embed the unknown probability models. Simulation study shows that the predictive FH method is more accurately predict FH sequences than the random or simple adaptive FH methods. We will further improve this proposed method to apply QoS control and MAC function development in OFDMA based wireless physical structures, especially maritime wireless data communications.

QoS Control Strategy Simulation and Analysis Based on DiffServ

As the development and applying of real-time multimedia such as VoIP, video conferencing and so on, the Internet is required to provide a better QoS support. However, current IP network can only provide ‘Best Effort’ service and can not satisfy different network multimedia traffic quality requirements. Based on the analysis DiffServ architecture and studies its control mechanism, the OPNET simulation design different ToS value in IP header of VoIP traffic, and apply WFQ scheduling algorithm on the bottleneck link. The simulation results compare jitter, delay, delay variation of different ToS value of VoIP traffic, and analyze relationship of QoS and ToS value in the IP network.

Next-generation QoS control architectures for distribution smart grid communication networks

This article presents a proposal for applying the ITU-T end-to-end QoS control architecture for next-generation networks to the distribution smart grid communication networks. We propose the use of a QoS broker device to enhance the QoS in the smart grid electrical distribution access domains by providing a centralization of QoS management. Our proposal takes decisions based on current network data traffic flows, existing QoS policies and customer service level agreements and facilitates interoperability with other technology domains in order to achieve seamless end-to-end QoS. The key feature of this end-toend QoS control is the mapping of QoS parameters mainly between broadband power line and wireless technologies that principally serve the distribution smart grid but it can be applied to other communication technologies as well.

Deploying Circuit Emulation Services (CES) Over EPON Using Preemptive Priority Medium Access Controller

Circuit Emulation Services (CES) technology has emerged as an option to mitigate traditional Time Division Multiplexing (TDM) circuits supporting legacy applications across managed packet networks and the Ethernet Passive Optical Network (EPON) is becoming a major technology for pervasive access. The primary benefits of CES over EPON (CESoEPON) are the low cost and simplicity of deployment to support all types of legacy TDM applications across EPONs. Thus, the QoS-guarantee for highly delay-sensitive services on EPONs could be enhanced. This paper investigates a preemptive priority transmission technique that works on MAC and PHY layer of downstream EPONs. The proposed novel scheme effectively reduces the frame queuing delay as well as jitter, so as to enhance precise time synchronization in EPONs. Through simulation experiments, we show that the proposed scheme achieves superior and precise QoS control compared to existing non-preemptive priority methods. A feasible implementation of the proposed solution is also addressed. Finally, we present a general conclusion of the paper as well as address the pros and cons for practical deployment in future works.

Wireless Hybrid QoS Architecture with an Enhancement of Fair Intelligent Congestion Control

More subtle and explicit QoS control mechanisms are required at the radio access level, even though the simple and scalable Differentiated Services (DiffServ) QoS control model is acceptable for the core of the network. At the radio access level, available resources are severely limited and the degree of traffic aggregation is not significant, thus rendering the DiffServ principles less effective. In this paper we present a suitable hybrid QoS architecture framework to address the problem. At the wireless access end, the local QoS mechanism is designed in the context of IEEE 802.11 WLAN with 802.11e QoS extensions; so streams of those session-based applications are admitted, established according to the traffic profile they require, and guaranteed. As the core in the Admission Control of the hybrid QoS architecture, the Fair Intelligent Congestion Control (FICC) algorithm is applied to provide fairness among traffic aggregates and control congestion at the bottleneck interface between the wireless link and the network core via mechanisms of packet scheduling, buffer management, feedback and adjustments. It manages effectively the overloading scenario by preventing traffic violation from uncontrolled traffic, and providing guarantee to the priority traffic in terms of guaranteed bandwidth allocation and specified delay.

The System Construction and the Implementation of QOS Control Mechanism in Intelligent Streaming Media

Abstract In the existing IP-based Internet, the real-time transmission of media streaming data is a hot issue of the current network application research. This paper constructs an intelligent streaming media system. To protect the important data in real time and improve the quality of service as far as possible, we have taken a variety of measures, including the scalable layered coding, the caching mechanism of the client and server, non-uniform scheduling strategy, early warning of non-uniform stream control and congestion control, non-uniform error control, etc.

Resource Control Model for QoS in the Trustworthy and Controllable Network

基于前期工作——可信可控网络体系结构TCNA(trustworthy and controllable network architecture),提出了一种QoS 资源控制模型(resource control model for QoS,简称RCMQ).该模型从网络可控角度将QoS 控制分为4层: QoS 决策层面、QoS 观测层面、QoS 接口层面和QoS 资源层面,模型部署包括独立集中的域内控制和一致性分布式控制.RCMQ 模型闭环控制结构保证了QoS 控制的有效性,而独立集中的QoS 决策层面使得模型具有可扩展性.最后,通过仿真实验验证了RCMQ 资源控制模型与InterServ 模型相比,能够提供更为稳定的QoS 传输,并且极大地减少了QoS 状态维护,同时也从侧面说明可信可控网络体系比传统TCP/IP 网络具有更高的可控性.;In this article, a Resource Control Model for QoS (RCMQ) is presented, based on the former work on Trustworthy and Controllable Network Architecture (TCNA). The QoS mechanisms are distributed into four logical planes in RCMQ: QoS decision plane, QoS discovery plane, QoS data plane, and QoS interface plane. Deployment of RCMQ includes independent and centralized resource control within an Autonomous System and consensus distributed control among ASes. RCMQ is scalable because it decouples all network level QoS control mechanisms from the data plane, and it is robust because RCMQ is a simple and effective close loop control structure. Finally RCMQ in SSFNet environment are implemented, and experimental results show that RCMQ can provide a more stable QoS transmission and maintain fewer flow states than InterServ, which from the other point of view proves that TCNA is more controllable.