Quality Of Service Definition Research Articles

QACDes: QoS-aware context-sensitive design of cyber-physical systems

There is a lot of confusion and ambiguity regarding the quantification of the Quality of Service (QoS) of a system, especially for cyber-physical systems (CPS) involved in automating or controlling the operations in built environments and critical urban infrastructures, such as office buildings, factories, transportation systems, smart cities, etc. In these cases, the QoS, as experienced by human users, depends on the context in which they (i.e., humans) interact with these systems. Traditionally, the QoS of a CPS has been defined in terms of absolute metrics. Such measures are unable to take into account the variations in performance due to contextual factors arising out of different kinds of human interactions. Further, the QoS of a CPS has typically been evaluated by comparing the performance of the actual, fully realized system with the given QoS constraints only after the actual system has been completely developed. In the case of faults in the design exposed by observed deviations from the QoS constraints due to unpredicted variations in the contextual factors, the system needs to be re-designed and re-developed from scratch. Due to the above-mentioned reason, the validation approach associated with the traditional QoS makes the design of CPS systems prohibitively expensive, impractical, as well as infeasible in numerous application areas, such as civil and engineering works, since it may not be possible to modify the system once developed beyond a certain extent. To that end, we propose a context-aware definition of QoS of a CPS which facilitates the design of robust systems as elaborated below. In this paper, we define QoS as a function of contextual factors. A CPS designed according to our QoS specifications would always satisfy the QoS irrespective of any possible changes in contextual factors resulting from many different human interactions that may occur during operation of the system. We also present QACDes - a novel framework that provides a formal mechanism for validating the design of a CPS with respect to the specified QoS constraints at the design phase as well as after the realization of the actual system. QACDes can validate any given CPS, irrespective of its application domain, against a QoS guarantee: (A) as early as even before the design phase by comparing the proposed model with a baseline model, or (B) after the realization of the actual system based on logs collected from running the actual system. We consider a lighting control system that manages the light switches - switching it on/off depending on contextual factors, such as the presence of occupants and time of the day. Using the lighting control system in a building as a use case, we analyze and demonstrate the effectiveness of our QoS definition as well as the QACDes framework against the performance metric measured in an actual fully-realized CPS.

On the classification of fog computing applications: A machine learning perspective

Currently, Internet applications running on mobile devices generate a massive amount of data that can be transmitted to a Cloud for processing. However, one fundamental limitation of a Cloud is the connectivity with end devices. Fog computing overcomes this limitation and supports the requirements of time-sensitive applications by distributing computation, communication, and storage services along the Cloud to Things (C2T) continuum, empowering potential new applications, such as smart cities, augmented reality (AR), and virtual reality (VR). However, the adoption of Fog-based computational resources and their integration with the Cloud introduces new challenges in resource management, which requires the implementation of new strategies to guarantee compliance with the quality of service (QoS) requirements of applications.In this context, one major question is how to map the QoS requirements of applications on Fog and Cloud resources. One possible approach is to discriminate the applications arriving at the Fog into Classes of Service (CoS). This paper thus introduces a set of CoS for Fog applications which includes, the QoS requirements that best characterize these Fog applications. Moreover, this paper proposes the implementation of a typical machine learning classification methodology to discriminate Fog computing applications as a function of their QoS requirements. Furthermore, the application of this methodology is illustrated in the assessment of classifiers in terms of efficiency, accuracy, and robustness to noise. The adoption of a methodology for machine learning-based classification constitutes a first step towards the definition of QoS provisioning mechanisms in Fog computing. Moreover, classifying Fog computing applications can facilitate the decision-making process for Fog scheduler.

Mapping QoE through QoS in an Approach to DDB Architectures

In the context of distributed databases (DDBs), the absence of mathematically well defined equations to evaluate quality of service (QoS), especially with statistical models, seems to have taken database community attention from the possible performance guarantees that could be handled by concepts related to quality of experience (QoE). In this article, we targeted the definition of QoE based on completeness of QoS to deal with decisions concerning with performance correction in a system level. This study also presents a statistical bibliometric analysis before the proposed model. The idea was to show the origin of first studies with correlated focus, which also have initial conceptualizations, and then propose a new model. This model concerns concise QoS definitions, grouped to provide a basis for QoE analysis. Afterward, it is foreseen that a DDB system will be able to autoevaluate and be aware of recovering situations before they happen.

A Survey of Medium Access Mechanisms for Providing QoS in Ad-Hoc Networks

In this survey we attempt to describe the Quality of Service (QoS) mechanisms employed by Medium Access Control (MAC) protocols designed for ad-hoc networks. We begin with background information: an overview of the related work, the definition of QoS and QoS-related metrics, a general description of contention-free and contention-based protocols for wireless networks, a discussion of issues affecting QoS provisioning in ad-hoc networks, as well as a novel classification of the QoS mechanisms. Then, each mechanism is briefly explained and implementation examples from different protocols are provided. Furthermore, a separate section is devoted to the completed and ongoing standardization work in the field. Afterwards, an extensive comparison of salient features, advantages and disadvantages of all described MAC mechanisms is given in order to guide future protocol designers. Finally, we comment on the most probable future research directions. Based on the presented survey, we observe that QoS provisioning is not only challenging but also a significant contemporary research problem. The protocol designs presented in the literature usually involve trade-offs between certain metrics, and currently there is no ideal solution which deals with all the issues affecting ad-hoc networks. Therefore, we trust that this survey will be of great help to designers of future QoS-aware protocols.

Policies for allocating performance impairment budgets among multiple IP providers

An important technical aspect of achieving end-to-end quality of service (QoS) in next generation networks refers to allocation of the total performance impairment budget (delay, jitter, packet loss) among multiple providers. In this article, we first propose a generic policy for allocating per-domain impairment budgets, relying on the set of performance metrics from service request and the rules for their composition on the multi-domain path. The objective is to provide end-to-end QoS through the set of heterogeneous domains, with different QoS models and definitions of service classes. The allocation of impairment budgets among multiple domains is then closely related to mapping of service classes between providers and selection of the most appropriate class for particular service in each domain. Based on the generic policy, we further derive examples of specific policies and evaluate them with respect to fulfillment of QoS objectives, fairness, adaptability and scalability. Evaluation tool implements a policy-based conformance matching scheme, which enforces selection of the domain class that most tightly matches with the required QoS.

A self-adjustment QoS architecture for wireless sensor networks

An architecture featured in quality of service (QoS) online self-adjusted measurement and control for wireless sensor networks (WSN) is proposed in this paper. Unlike traditional end to end (E2E) QoS definition, many new characteristics are presented in WSN, especially data-centric and application driven. Based on exploration of WSN QoS definition and typical traffic model, we design a dynamic QoS guarantees platform, which achieves online protocol self-adjustment to get optimization performance. The architecture is verified by a practical system designed for environment monitoring.

QUALİTY OF SERVİCE AND SECURİTY CONTROL FOR CLUSTER-BASED WİRELESS SENSOR NETWORKS

In this study, we investigate security and quality of service (QoS) issues in clusterbased wireless sensor networks (WSN). Our QoS definition consists of four attributes, which are spatial resolution, coverage, network lifetime and packet collisions. And, the security scope of our study is limited by message integrity and authentication. We present a novel control strategy to maintain desired QoS and security levels during the entire operation of a cluster-based sensor network. Compared to our previous work [1], the proposed method provides much better results for three of the four service quality attributes. This study also presents a method for determining the best tradeoff between security and spatial resolution for cases where network capacity is not sufficient to support required security and resolution levels. This method is based on a heuristic algorithm that we developed to solve an optimization problem.

Preemption-Aware Instantaneous Request Call Routing for Networks With Book-Ahead Reservation

This paper presents a new preemption-aware quality of service (QoS) routing algorithm for instantaneous request (IR) call connections in a QoS-enabled network where resources are shared between IR and book-ahead (BA) call connections. BA reservation, which confirms the availability of resources in advance, is a highly attractive technique for time sensitive applications that require high amount of bandwidth with guaranteed QoS. One of the major concerns for the implementation of BA reservation is the need for preemption of on-going IR calls to accommodate BA calls when resource scarcity arises. Preemption disrupts service continuity of on-going calls which is considered as severely detrimental from users' perceived QoS definition found in recent studies. Existing QoS routing algorithms focus on resource conservation or load balancing as the key objective to attain in addition to guaranteed QoS. No works have yet focused on the preemption problem of on-going IR calls at routing stage in the presence of BA calls. We present a mathematical formulation to compute the preemption probability of an incoming IR call at routing stage based on the current IR and future BA load information. We propose a routing strategy by formulating a link cost function comprising of the calculated preemption probability of the incoming IR call and hop count. Simulation results confirm that QoS routing based on the proposed link cost function significantly outperforms widely recommended shortest path and widest path routing algorithms in terms of IR call preemption and blocking rate. The proposed approach also yields higher network utilization and IR effective throughput.

Practical algorithms for scheduling video data in a local area network environment

Simultaneous transmission of multiple high quality video streams from a server to the clients is becoming an increasingly important class of traffic in a network of workstations or cluster environment. With a powerful symmetric multiprocessor (SMP) as the server and a high-speed network, such transmission is practicable from a hardware point of view. However, the actual construction of such a video data server system entails tackling a number of difficult problems related to the provision of strict quality of service (QoS) guarantees. Among others, the smoothing and scheduling of multiple video packet streams are two crucial issues. Smoothing is concerned with reducing the rate variability of video streams in view of the fact that video data are usually compressed in a variable bit rate fashion. Scheduling is important to guarantee the requested QoS levels while maximizing the utilization of the resources. Although much work on smoothing has been done, it is not clear which scheduling scheme is suitable for multiplexing smoothed video data to the network. In this paper we present an extensive performance study of the EDF and RM scheduling algorithms which are modified to provide QoS guarantees for smoothed video data. With a probabilistic definition of QoS, admission control conditions are incorporated into the two algorithms. Furthermore, a counter-based scheduling module is included as the core scheduling mechanism which adaptively adjusts the actual QoS levels assigned to requests. Our theoretical analysis of the two modified algorithms, called QEDF and QRM, shows that the QRM algorithm is more robust than the QEDF algorithm for different workload and utilization conditions. We also propose to use a new metric called meta-QoS to quantify the overall performance of a packet scheduler given a set of simultaneous requests. In our experiments based on an SMP-based Linux platform, we find that the QRM algorithm can sustain a rather stable level of meta-QoS even when the workload and utilization levels are increased. On the other hand, the QEDF algorithm, due to its conservative admission control policy, is found to be not suitable for a high level of utilization and a large number of requests. In view of the lower complexity of the QRM algorithm, it seems that the QRM approach is a more suitable candidate for packet scheduling in the client-server environment considered in our study.

A Model for Availability of Quality of Service in Distributed Multimedia Systems

In this paper we introduce a new model for the definition and the implementation of quality of service (QoS) in distributed multimedia systems. The model provides both the users and the provider/manager of the system with a framework for the high level description of the system's configuration and operation, as well as with an application/user specific definition of QoS. The model maps this high level QoS description to quality requirements for the individual resources that compose the overall service. The implementation of the QoS of the overall service is done by providing probability of availability guarantees for certain levels of QoS. Given some constraints on the total assets available for the implementation of a specific service, the model optimally allocates these assets to the system resources in order to implement a specific user/application QoS profile. The model is reduced to a General Asset Allocation Problem (GA2P) and we solve the GA2P in a provably optimal way for a wide range of realistic services.

Quality of service in telecommunications. I. Proposition of a QoS framework and its application to B-ISDN

The the quality of service (QoS) concept is becoming an ever more important issue in telecommunication and computer communication. The article focuses on the QoS notion and concept. The definition of QoS in the International Telecommunications Union-Telecommunications Sector (ITU-T) recommendations and the International Standards Organization (ISO) standards is analysed. Little is known about the asynchronous transfer mode (ATM) performance requirements of the broadband integrated services digital network (B-ISDN) services, especially for multimedia applications. This is because the ATM performance requirements of multimedia applications depend not only on the diverse QoS requirements from application and user, but also on the protocol stacks and scheduling in end systems. Therefore, in order to guarantee QoS to the user, it is necessary to introduce a set of QoS parameters whose properties indicate the nature and requirements of the layered protocol stack. We describe how a proposed QoS framework can be applied to B-ISDN as a specific network. The QoS aspects related to B-ISDN signaling (the control plane) and the QoS aspects related to layer and plane management (the management plane) are described. We also describe how the QoS framework resides in a protocol stack and works together with the B-ISDN network management and signaling.