Quantitative Quality Of Service Research Articles

An adaptive failure detector based on quality of service in peer-to-peer networks.

The failure detector is one of the fundamental components that maintain high availability of Peer-to-Peer (P2P) networks. Under different network conditions, the adaptive failure detector based on quality of service (QoS) can achieve the detection time and accuracy required by upper applications with lower detection overhead. In P2P systems, complexity of network and high churn lead to high message loss rate. To reduce the impact on detection accuracy, baseline detection strategy based on retransmission mechanism has been employed widely in many P2P applications; however, Chen's classic adaptive model cannot describe this kind of detection strategy. In order to provide an efficient service of failure detection in P2P systems, this paper establishes a novel QoS evaluation model for the baseline detection strategy. The relationship between the detection period and the QoS is discussed and on this basis, an adaptive failure detector (B-AFD) is proposed, which can meet the quantitative QoS metrics under changing network environment. Meanwhile, it is observed from the experimental analysis that B-AFD achieves better detection accuracy and time with lower detection overhead compared to the traditional baseline strategy and the adaptive detectors based on Chen's model. Moreover, B-AFD has better adaptability to P2P network.

Web Service Composition Optimization Based on Improved Artificial Bee Colony Algorithm

Web service composition is a hot and active research area in service oriented architecture (SOA). With highly developing of Web service, users pay more and more attention to quality of service (QoS). In order to obtain high comprehensive quality composite services, an optimizing method was presented in this paper. Firstly, build representative QoS properties quantitative models and QoS aggregation models, then proposed the mathematical model of Web service composition optimizing problem. Secondly, presented an improved artificial bee colony algorithm (I-ABC) and applied to solving Web service composition optimizing problem, I-ABC performance was enhanced by importing taboo strategy and chaos. Finally, some simulation experiments are given, and the results proved I-ABC has perfect performance in Web service composition optimizing than ABC

Context-aware end-to-end QoS diagnosis and quantitative guarantee based on Bayesian network

To support quality of service (QoS) management on current Internet working with best effort, we bring forth a systematic approach for end-to-end QoS diagnosis and quantitative guarantee. For QoS diagnosis, we take contexts of a service into consideration in a comprehensive way that is realized by exploiting causal relationships between a QoS metric and its contexts with the help of Bayesian network (BN) structure learning. Context discretization algorithm and node ordering algorithm are proposed to facilitate BN structure learning. The QoS metric is diagnosed to be causally related to its causal contexts, and the QoS metric can be quantitatively guaranteed by its causal contexts. For quantitative QoS guarantee, those causal relationships are first modeled quantitatively by BN parameter learning. Then, the QoS metric is guaranteed to certain value with a probability given its causal contexts tuned to suitable values, that is, quantitative QoS guarantee is reached. Simulations with three sequential stages: context discretization, QoS diagnosis and quantitative QoS guarantee, on a peer-to-peer (P2P) network, are discussed and our approach is validated to be effective.

Online Packet Loss Measurement and Estimation for VPN-Based Services

When provisioning quantitative quality of service (QoS) for virtual private network (VPN) services over packet switched networks, parameters such as packet loss, delay, and delay jitter, besides the required bandwidth, have to be guaranteed. While the bandwidth is relatively easier to guarantee, maintaining a value of the packet loss parameter below a preset value presents great interests but serious difficulties. One of the key issues is to link the stochastic characteristics of the input process to the packet loss probability (PLP), i.e., how one can accurately estimate the PLP based on measurements of the input process. This is crucial for building transducers for control loops meant for keeping the packet loss parameter within the guaranteed limits as specified by the service level agreement (SLA). Although the estimation of the PLP has been studied by many researchers, little has been done in regard to the estimators of the packet loss parameter such that the latter can be used in online applications. This paper studies the PLP estimation problem from a transducer and, hence, a control system perspective, and evaluates the quality of the proposed solutions through live network experimental data. Two asymptotic estimation formulas for loss probability are derived by applying the large deviation theory (LDT) on the buffer overflow probability and proposed as mathematical relations to be used by the online transducer.

FP/FIFO scheduling: coexistence of deterministic and probabilistic QoS guarantees

Distributed Computing and Networking In this paper, we focus on applications having quantitative QoS (Quality of Service) requirements on their end-to-end response time (or jitter). We propose a solution allowing the coexistence of two types of quantitative QoS garantees, deterministic and probabilistic, while providing a high resource utilization. Our solution combines the advantages of the deterministic approach and the probabilistic one. The deterministic approach is based on a worst case analysis. The probabilistic approach uses a mathematical model to obtain the probability that the response time exceeds a given value. We assume that flows are scheduled according to non-preemptive FP/FIFO. The packet with the highest fixed priority is scheduled first. If two packets share the same priority, the packet arrived first is scheduled first. We make no particular assumption concerning the flow priority and the nature of the QoS guarantee requested by the flow. An admission control derived from these results is then proposed, allowing each flow to receive a quantitative QoS guarantee adapted to its QoS requirements. An example illustrates the merits of the coexistence of deterministic and probabilistic QoS guarantees.

Experimental Characterization and Modeling of the QoS for Real Time Audio and Video Transmission

Multimedia applications have intrinsic quality of service (QoS) requirements. However, a quantitative evaluation of the QoS offered by the network is rarely realized. Furthermore, the traditional methods for ensuring an end-to-end QoS rely on mechanisms provided by the distribution network. In this paper we propose a new quantitative QoS model that is validated by extensive experimental characterization of the QoS dependence on traffic parameters. This model is then used to design a QoS restoration technique that is independent of special resources available in the distribution network.

Automobile Drivers' Perceptions of Service Quality on Urban Streets

The Highway Capacity and Quality of Service Committee of TRB, which oversees the development of the Highway Capacity Manual, has formally recognized a need to improve the current level-of-service (LOS) methodologies. Among the concerns about the methodologies is the extent to which LOS estimates correspond to road users' perceptions. In recognition of these concerns, the objectives of this study were to ( a) develop and test a methodology to obtain drivers' opinions with regard to urban street quality of service (QOS), ( b) apply the methodology to identify the factors that affect drivers' perceptions of QOS on urban streets, and ( c) provide a qualitative foundation for the development of quantitative QOS tools that are based on the perceptions of drivers. This study used an in-vehicle field approach to determine the factors that affect automobile drivers' perceptions of service quality on urban streets. While driving on a preselected route, 22 participants in four cities were asked to speak aloud about their driving experience and the factors that influenced their perception of service quality. Afterward, drivers also completed a written questionnaire. The drivers expressed their opinions about a wide range of issues, including simple observations, more detailed evaluations, and broad concerns related to the roadway environment. From the drivers' comments, 40 factors were identified as relevant to their perception of service quality on urban streets. The authors believe that by identifying a wide range of factors that influence drivers' perceptions of service quality on urban streets, this study has increased the knowledge and understanding of the needs and values of automobile drivers on urban streets and has laid the groundwork for future studies aimed at developing quantitative QOS tools and models.

A service model for guaranteeing packet loss bounds in differentiated services architectures

Differentiated Services (DiffServ) is a proposed architecture for the Internet in which various applications are supported using a simple classification scheme. Packets entering the DiffServ domain are marked depending on the packets' class. Premium service and Assured service are the first two types of services proposed within the DiffServ architecture other than the best effort service. Premium service provides a strict guarantee on users' peak rates, hence delivering the highest Quality of Service (QoS). However, it expected to charge at high rates and also to have low bandwidth utilization. The Assured service provides high priority packets with preferential treatment over low priority packets but without any quantitative QoS guarantees. In this paper, we propose a new service, which we call the Loss bound Guaranteed (LG) service for DiffServ architectures. This service can provide a quantitative QoS guarantee in terms of loss rate. A measurement-based admission control scheme and a signaling protocol are designed to implement the LG service. An extensive simulation model has been developed to study the performance and viability of the LG service model. We have tested a variety of traffic conditions and measurement parameter settings in our simulation. The results show that the LG service can achieve a high level of utilization while still reliably keeping the traffic within the maximum loss rate requirement. Indeed, we show that the DiffServ architecture can provide packet-loss guarantees without the need for explicit resource reservation.