Quality Of Service Management Framework Research Articles

Learning-based resilience guarantee for multi-UAV collaborative QoS management

Unmanned and intelligent technologies are the future development trend in the business field. It is of great significance for the connotation analysis and application characterization of massive interactive data. Particularly, during major epidemics or disasters, how to provide business services safely and securely is crucial. Specifically, providing users with resilient and guaranteed communication services is a challenging business task when the communication facilities are damaged. Unmanned aerial vehicles (UAVs), with flexible deployment and high maneuverability, can be used to serve as aerial base stations (BSs) to establish emergency networks. However, it is challenging to control multiple UAVs to provide efficient and fair communication quality of service (QoS) to users due to their limited communication service capabilities. In this paper, we propose a learning-based resilience guarantee framework for multi-UAV collaborative QoS management. We formulate this problem as a partial observable Markov decision process and solve it with proximal policy optimization (PPO), which is a policy-based deep reinforcement learning method. A centralized training and decentralized execution paradigm is used, where the experience collected by all UAVs is used to train the shared control policy. Each UAV takes actions based on the partial environment information it observes. In addition, the design of the reward function considers the average and variance of the communication QoS of all users. Extensive simulations are conducted for performance evaluation. The simulation results indicate that (1) the trained policies can adapt to different scenarios and provide resilient and guaranteed communication QoS to users, (2) increasing the number of UAVs can compensate for the lack of service capabilities of UAVs, (3) when UAVs have local communication service capabilities, the policies trained with PPO have better performance compared with the policies trained with other algorithms.

Horizon: a QoS management framework for SDN-based data center networks

Data center networks (DCNs), which serve as the infrastructural backbone of big data, have been receiving increasing attention recently. To improve the service quality of data centers, researchers have been working on congestion control, network monitoring, and performance optimization. However, most such works focus on user-centric service quality, which means that the quality of network service itself is not factored into the quality of service (QoS) problem. In this study, we illustrate the problem of data center operations and management as a new type of QoS that is the foundation of user-centric QoS implementation. Inspired by traditional works on network performance optimization, we define the quality of network service in a software-defined networking (SDN)-based DCN and develop a framework called Horizon as the architecture of our QoS solution. This framework comprises a Markov-process-based method to predict link popularity, and we use SDN technology to monitor network status. We implement the proposed method, and the experimental results indicate that Horizon can relieve congestion in DCNs to meet QoS requirements. The experimental results show that our approach has a similar performance to the optimal solution. When compared with the ECMP approach, our approach has a much lower latency. The results also show that the proposed approach is effective in terms of network congestion control.

QoS Support in SGD-Based High Throughput Satellite Networks

This paper proposes a quality of service (QoS) management framework for high throughput satellite (HTS) systems using extremely high frequency (EHF) frequency bands, which can achieve high capacity provided that feeder link outage events caused by severe weather conditions can be properly counteracted. To this regard, smart gateway diversity architectures implementing advanced gateway handover procedures are certainly attractive, although they can only partly mitigate the negative effects of adverse weather conditions in terms of packet losses, delays, and jitters, which significantly degrade the performance of delay-sensitive and delay-insensitive traffic flows. To cope with these technical challenges, we propose an incremental rerouting scheme to control congestion events because of capacity reduction during the transient phase, consisting of offloading high-priority QoS traffic flows from the affected gateway towards gateways operating in more favorable conditions. Moreover, we apply inter-flow network coding at the gateways to protect delay-insensitive flows from packet losses occurring during feeder link outage. Finally, extra capacity is reserved at the gateways to handle the additional traffic resulting from gateway handover. The theoretical analysis (validated by simulation campaigns) allowed characterizing network coding performance and confirming the potentialities of our QoS management framework for HTS systems.

QoS4IVSaaS: a QoS management framework for intelligent video surveillance as a service

Quality of service (QoS) is critical for real-time intelligent video surveillance as a service (IVSaaS) platform, which is both computation intensive and data intensive by nature. However, there is scarce work on a QoS framework for IVSaaS platform. In this paper, we propose QoS for intelligent video surveillance as a service, a QoS framework to make computing resources highly available. In the framework, multiple metrics such as throughput, loads of CPU/GPU, memory and IO are taken into account with different time series models to enhance the adaptivity of different video services. A model selection algorithm is proposed to choose the model that achieves the best performance under various error indicators. At the same time, a resource abnormality detection algorithm is designed to detect anomalies when a service is underperformed. Evaluation results show that the proposed QoS framework can successfully ensure QoS by dynamically scheduling computing resources.

A cognitive QoS management framework for WLANs

Due to the precipitous growth of wireless networks and the paucity of spectrum, more interference is imposed to the wireless terminals which constraints their performance. In order to preserve such performance degradation, this paper proposes a framework which uses cognitive radio techniques for quality of service (QoS) management of wireless local area networks (LANs). The framework incorporates radio environment maps as input to a cognitive decision engine that steers the network to optimize its QoS parameters such as throughput. A novel experimentally verified heuristic physical model is developed to predict and optimize the throughput of wireless terminals. The framework was applied to realistic stationary and time-variant interference scenarios where an average throughput gain of 344% was achieved in the stationary interference scenario and 70% to 183% was gained in the time-variant interference scenario.

Semantic-based QoS management in cloud systems: Current status and future challenges

Cloud Computing and Service Oriented Architectures have seen a dramatic increase of the amount of applications, services, management platforms, data, etc. gaining momentum for the necessity of new complex methods and techniques to deal with the vast heterogeneity of data sources or services. In this sense Quality of Service (QoS) seeks for providing an intelligent environment of self-management components based on domain knowledge in which cloud components can be optimized easing the transition to an advanced governance environment. On the other hand, semantics and ontologies have emerged to afford a common and standard data model that eases the interoperability, integration and monitoring of knowledge-based systems. Taking into account the necessity of an interoperable and intelligent system to manage QoS in cloud-based systems and the emerging application of semantics in different domains, this paper reviews the main approaches for semantic-based QoS management as well as the principal methods, techniques and standards for processing and exploiting diverse data providing advanced real-time monitoring services. A semantic-based framework for QoS management is also outlined taking advantage of semantic technologies and distributed datastream processing techniques. Finally a discussion of existing efforts and challenges is also provided to suggest future directions.

A Scalable Framework for Policy-based QoS Management in SOA Environments

The successful integration of the Service Oriented Architecture (SOA) in large distributed environments greatly depends on their support of quality of service (QoS) management. The aim of QoS management is to guarantee diverse QoS levels to users issuing requests from a variety of platforms and underlying networks. In this paper, we present our policy-based framework for QoS management in SOA environment with both usual and mobile users. The framework is based on a federation of QoS Brokers that are in charge of mediating between service requestors and service providers, and carrying out various QoS management operations. We describe an auction-based ranking algorithm of functionally equivalent services, which ranks services according to their ability to fulfill the service requestor QoS requirements. The brokers are also in charge of handling appropriately service requests from mobile users equipped with various handheld devices.

Wireless industrial sensor networks: Framework for QoS assessment and QoS management

Abstract This paper presents a framework that addresses Quality of Service (QoS) for industrial wireless sensor networks as a real-time measurable set of parameters within the context of feedback control, thereby facilitating QoS management. This framework is based on examining the interaction between the industrial control processes and the wireless network. Control theory is used to evaluate the impact of the control/communication interaction, providing a methodology for defining, measuring, and quantifying QoS requirements. An example is presented illustrating the wireless industrial sensor network (WISN) QoS management framework for providing dynamic QoS control within WISN. The example focuses on WISN operating in a time-varying RF interference environment in order to manage application-driven QoS latency constraints.

Quality of service management framework for dynamic chaining of geographic information services

Dynamic chaining of geographic information services (geo-services) is gaining popularity as a new paradigm for evolving flexible geo-information systems and for providing on-demand access to geo-information. In dynamic chaining, disparate geo-services are discovered and composed at run time to yield more elaborate functionality and create value-added geo-information. Common approaches to service chaining discover and compose disparate geo-services based on the functional capability of individual geo-services. The primary concern of common approaches is thus the emergent behavior of the resulting composite geo-service. However, as geo-services become mundane and take on a greater and more strategic role in mission critical processes, deliverable quality of service (QoS) becomes an important concern. QoS concerns operational characteristics of a service that determine its utility in an application context. To address pertinent QoS requirements, a new approach to service chaining becomes necessary. In this paper we propose a QoS-aware chaining approach in which geo-services are discovered, composed and executed considering both functional and QoS requirements. We prescribe a QoS management framework that defines fundamental principles, concepts and mechanisms which can be applied to evolve an effective distributed computing platform for QoS-aware chaining of geo-services – the so-called geo-service infrastructure. The paper also defines an extensible QoS model for services delivered by dynamic compositions of geo-services. The process of orthophoto generation is used to demonstrate the applicability of the prescribed framework to service-oriented geographic information processing.

End-to-End QoS Resource Management for an IP-Based DWDM Access Network

The ever-increasing use of broad-band Internet and complex multimedia applications is pushing fiber closer and closer to the homes. Within the European project IST HARMONICS (Hybrid Access Reconfigurable Multi-wavelength Optical Networks for IP-based Communication Services), an optical access feeder network and resource management framework were developed that tackle this demand for bandwidth and the desire to stimulate the convergence of last-mile access technologies. To cope with the lack of bandwidth in the access and last-mile networks and the different needs of applications and users, the developed management system provides end-to-end quality of service (QoS) while integrating multiple technologies. In this paper, a detailed overview of the end-to-end QoS management framework and novel time slot/wavelength MAC protocol for the optical feeder network is given. End-to-end QoS is based on Differentiated services (DiffServ) at layer 3, various QoS supporting technologies at layer 2, and QoS mappings between both layers. The paper will also focus on the field trial results of the HARMONICS project and give some guidelines for possible problems and solutions in this area.

차별화 서비스망을 위한 정책 기반 서비스 품질 관리 모델

차별화 서비스(DiffServ)는 효율적이며 규모성을 갖는 방법으로 서비스 품질(QoS)을 제공하는 기술이다. 그러나, 현재의 차별화 서비스 규격들은 완전한 QoS 관리 프레임워크와 구현 모델의 제공에는 취약한 실정이다. 본 논문은 차별화 서비스 망의 QoS를 관리하기 위하여 차별화 서비스 정책을 지원하는 정책 기반 차별화 서비스 QoS 관리 모델을 제안한다. 이 모델을 모델-뷰-컨트롤러(MVC) 구조를 따르며, EJB(Enterprise JavaBeans) 기술에 기반을 두고 있다. 우리의 모델에서 상위 레벨 차별화 서비스 QoS 정책들은 XML 스키마를 갖는 유효한 XML 문서들로 표현되고 EJB 기반 정책 서버 내에 하위 레벨 EJB 정책 번들로 변환된다. QoS 정책을 정의하기 위해 필요한 라우팅 형상과 라우터의 역할 정보 검출은 SNMP MIB-II를 사용하고, QoS 정책 분배와 모니터링은 SNMP DiffServ MIB를 사용한다. Differentiated Services (DiffServ) is a technique to provide Quality of Service (QoS) in an efficient and scalable way. However, current DiffServ specifications have limitations in providing the complete QoS management framework and its implementation model. This paper proposes a policy-based QoS management model that supports DiffServ policies for managing QoS of DiffServ networks. The management model conforms to Model-View-Controller (MVC) architecture, and is based on Enterprise JavaBeans (EJBs) technologies. In our model, high-level DiffServ QoS policies are represented as valid XML documents with an XML Schema and are translated to low-level EJB policy beans in the EJB-based policy server. The routing topology and role information required to define QoS policies is discovered by using SNMP MIB-II, and the QoS policy distribution and monitoring is accomplished by using SNMP DiffServ MIB.

Distributed QoS monitoring and edge-to-edge QoS aggregation to manage end-to-end traffic flows in Differentiated Services networks

The Differentiated Services (DiffServ) framework has been proposed by the IETF as a simple service structure that can provide different Quality of Service (QoS) to different classes of packets in IP networks. IP packets are classified into one of a limited number of service classes, and are marked in the packet header for easy classification and differentiated treatments when transferred within a DiffServ domain. The DiffServ framework defines simple and efficient QoS differentiation mechanisms for the Internet. However, the original DiffServ concept does not provide a complete QoS management framework. Since traffic flows in IP networks are unidirectional from one network point to the other and routing paths and traffic demand get dynamically altered, it is important to monitor end-to-end traffic status, as well as traffic status in a single node. This paper suggests a distributed QoS monitoring method that collects the statistical data of each service class in every DiffServ router and calculates edge-to-edge QoS of the aggregated IP flows by combining routing topology and traffic status. A formal modeling of edge-to-edge DiffServ flows and algorithms for aggregating edge-to-edge QoS is presented. Also an SNMP-based QoS management prototype system for DiffServ networks is presented, which validates our QoS management framework and demonstrates useful service management functionality.

THE AMARANTH FRAMEWORK: POLICY-BASED QUALITY OF SERVICE MANAGEMENT FOR HIGH-ASSURANCE COMPUTING

System resource management for high-assurance applications such as the command and control of a battle group is a complex problem. These applications often require guaranteed computing services that must satisfy both hard and soft deadlines. Over time, their resource demands can also vary significantly with bursts of high activity amidst periods of inactivity. A traditional solution has been to dedicate resources to critical application tasks and to share resources among non-critical tasks. With the increasing complexity of high-assurance applications and the need to reduce system costs, dedicating resources is not a satisfactory solution. The Amaranth Project at Carnegie Mellon is researching and developing a framework for allocating shared resources to support multiple quality of service (QoS) dimensions and to provide probabilistic assurances of service. This paper is an overview of the Amaranth framework for policy-based QoS management, the current results from applying the framework, and the future research directions for the Amaranth project.

A CORBA-based quality of service management framework for distributed multimedia services and applications

For distributed multimedia services, it is essential that quality of service be guaranteed system-wide, including end systems, communication systems, and networks. Although many researchers have addressed issues of QoS management, little attention has so far been paid to the QoS management services in distributed multimedia services and applications. To address this deficiency, we have designed a layered model for end-to-end QoS management called the QoS management framework. Our framework, which is CORBA-based, includes a generic QoS MIB for the QoS parameterization of various multimedia services and the services needed to perform various QoS functions. A key component of this framework is the QoS management service object (QMSO), which orchestrates resources at endpoints, coordinating resource management across layer boundaries. Services such as translation, monitoring, admission, and negotiation are provided by the QMSO. To validate this concept, we have developed a QoS management system for managing and controlling the QoS of a distributed multimedia system called MAESTRO. The QoS management system has been implemented through CORBA objects and provides an interface to multimedia applications, which can be dynamic negotiation and renegotiation of QoS by users. Some performance results in QoS negotiation and renegotiation are also presented.

An Approach to Quality of Service Management in Distributed Multimedia Application: Design and an Implementation

Most work related to quality of service (QoS) is concerned with individual system components, such as the operating system or the network. However, to support distributed multimedia applications, the entire distributed system must participate in providing the guaranteed performance levels. In recognition of this, a number of QoS architectures have been proposed to provide QoS guarantees. The mechanisms and schemes proposed by those architectures are used in a rather static manner since the involved entities, e.g., the network, sender and receiver, are known before the connection (call) set-up phase. In contrast to these architectures, we propose a general QoS management framework which supports the dynamic choice of a configuration of system components to support the QoS requirements for the user of a specific application. We consider different possible system configurations and select the most appropriate one depending on the desired QoS and the available resources. In this paper we present an overview of this general frameworks especially, we concentrate on QoS negotiation and adaptation mechanisms. To show the feasibility of this approach, we designed and implemented a QoS manager for distributed multimedia presentational applications, such as news-on-demand. The negotiation and adaptation mechanisms which are supported by the QoS manager are specializations of the general framework. The proposed framework allows to improve the utilization of system resources, and thus to increase the system availability; it also allows to recover automatically, if this is possible, from QoS degradations. Furthermore, it provides the flexibility to incorporate different resource reservation schemes and scheduling policies, and to accommodate new system component technologies.