A context-aware decision engine for content adaptation

Building a good content adaptation service for mobile devices poses many challenges. To meet these challenges, this quality-of-service-aware decision engine automatically negotiates for the appropriate adaptation decision for synthesizing an optimal content version.     

A Flexible Content Adaptation System Using a Rule-Based Approach

Content adaptation is an important technique for mobile devices. Existing content adaptation systems have been developed with specific adaptation goals. In this paper, we present an extensible content adaptation system, Xadaptor. We take a rule-based approach to facilitate extensible, systematic, and adaptive content adaptation. It integrates adaptation mechanisms for various content types and organizes them into the rule base. Rules are invoked based on the individual client information. We classify HTML page objects into structure, content, and pointer objects. Existing content adaptation techniques mainly focus on content objects and do not consider adaptation for structure and pointer objects. In Xadaptor, novel adaptation techniques for the structure object HTML table have been developed. We use fuzzy logic to model the adaptation quality and guide the adaptation decision. To demonstrate the feasibility of our approach, we have implemented a prototype system. Experimental studies show that Xadaptor is capable of on-the-fly content adaptation and is easily extensible     

Specification,Mapping and Control for QoS Adaptation

In this paper we describe a fuzzy-control approach for quality of service (QoS) adaptation, needed in distributed multimedia applications. QoS adaptation is necessary (a) due to sudden variations in network resource availability, especially in the case of Internet, and (b) due to multiple applications requiring shared resource such as bandwidth. To solve the problem of QoS adaptation, several sub-problems need to be considered: (1) mapping of user perception and different combinations of application QoS values onto a uniform quality metric, (2) estimation, control and adjustment of application QoS parameters in case of network and other resource congestion, and (3) enforcement algorithm which reacts according to adapted QoS parameters. Our approach is to solve the QoS adaptation using the integration of (a) quality degree function, which maps the application QoS parameters into a metric, called quality degree, (b) fuzzy controller, which controls, estimates and adjusts the application QoS parameters according to resource availability, and (c) filter algorithms, which are the services to enforce the adapted QoS parameters. The quality degree function associates quality degree as the quality measure with different combinations of application QoS values. This function is influenced by the users perception of quality. The fuzzy control takes the results of the quality degree function, estimates the new quality degree and its corresponding quality level, predicts the new application QoS parameters, and adjusts them. The results of the adapted QoS parameters are then used by the filter algorithms to enforce the changes, proposed by the fuzzy controller, by allocating bandwidth to the application according to its QoS parameter values. We have implemented and applied the quality degree function, the fuzzy controller, and the filter algorithms to the video distribution system (VDS). The results of VDS over the local area network show that (1) the target system improves user perceived QoS at the receivers, and (2) the bandwidth utilization increases significantly when using our fuzzy-control approach for QoS adaptation.     

Providing QoS through machine-learning-driven adaptive multimedia applications

We investigate the optimization of the quality of service (QoS) offered by real-time multimedia adaptive applications through machine learning algorithms. These applications are able to adapt in real time their internal settings (i.e., video sizes, audio and video codecs, among others) to the unpredictably changing capacity of the network. Traditional adaptive applications just select a set of settings to consume less than the available bandwidth. We propose a novel approach in which the selected set of settings is the one which offers a better user-perceived QoS among all those combinations which satisfy the bandwidth restrictions. We use a genetic algorithm to decide when to trigger the adaptation process depending on the network conditions (i.e., loss-rate, jitter, etc.). Additionally, the selection of the new set of settings is done according to a set of rules which model the user-perceived QoS. These rules are learned using the SLIPPER rule induction algorithm over a set of examples extracted from scores provided by real users. We will demonstrate that the proposed approach guarantees a good user-perceived QoS even when the network conditions are constantly changing.     

Rule-based Adaptation of Web Information Systems

Mobile devices provide a variety of ways to access information resources available on the Web and a high level of adaptability to different aspects of the context (such as the device capabilities, the network QoS, the user preferences, and the location) is strongly required in this scenario. In this paper, we present a rule-based approach supporting the automatic adaptation of content delivery in Web Information Systems. The approach relies on the general notions of profile and configuration. The former is used to model a variety of context characteristics in a uniform way. The latter describes, in abstract terms, how to build the various levels of a suitable Web interface (content, navigation and presentation). We propose an original notion of adaptation rule that can be used to specify, in a declarative way, how to build a configuration that satisfies the requirements of adaptation for a profile. The evaluation process defined for these rules supports: (1) the handling of many separately specified adaptation requirements according to different aspects of the context, possibly not fixed in advance, and (2) their integration into one coherent recipe for adaptation. We also describe the architecture and functionality of a prototype implementing the proposed approach and illustrate experimental results supporting its flexibility and efficiency. A preliminary version of this paper appears in the Proceedings of Seventh International Conference on Mobile Data Management (MDM’06) Nara, Japan, May 10–12, 2006.     

Hierarchical multiobjective routing in Multiprotocol Label Switching networks with two service classes: a heuristic solution

Modern multiservice network routing functionalities have to deal with multiple, heterogeneous and multifaceted Quality of Service (QoS) requirements. A heuristic approach devised to find "good" solutions to a hierarchical multiobjective alternative routing optimization problem in Multiprotocol Label Switching networks with two service classes (and different types of traffic flows in each class), namely QoS and Best Effort services, formulated within a hierarchical network-wide optimization framework, is presented. This heuristic solution is based on a bi-objective constrained shortest path model and is applied to a test network used in a benchmarking case study. An experimental study based on analytic and discrete event simulation results is presented, allowing for an assessment of the quality of results obtained with this new heuristic solution for various traffic matrices. A dynamic version of the routing method is formulated and its performance with the same case study network is analysed.     

Probabilistic approach for QoS-aware recommender system for trustworthy web service selection

We present a QoS-aware recommender approach based on probabilistic models to assist the selection of web services in open, distributed, and service-oriented environments. This approach allows consumers to maintain a trust model for each service provider they interact with, leading to the prediction of the most trustworthy service a consumer can interact with among a plethora of similar services. In this paper, we associate the trust in a service to its performance denoted by QoS ratings instigated by the amalgamation of various QoS metrics. Since the quality of a service is contingent, which renders its trustworthiness uncertain, we adopt a probabilistic approach for the prediction of the quality of a service based on the evaluation of past experiences (ratings) of each of its consumers. We represent the QoS ratings of services using different statistical distributions, namely multinomial Dirichlet, multinomial generalized Dirichlet, and multinomial Beta-Liouville. We leverage various machine learning techniques to compute the probabilities of each web service to belong to different quality classes. For instance, we use the Bayesian inference method to estimate the parameters of the aforementioned distributions, which presents a multidimensional probabilistic embodiment of the quality of the corresponding web services. We also employ a Bayesian network classifier with a Beta-Liouville prior to enable the classification of the QoS of composite services given the QoS of its constituents. We extend our approach to function in an online setting using the Voting EM algorithm that enables the estimation of the probabilities of the QoS after each interaction with a web service. Our experimental results demonstrate the effectiveness of the proposed approaches in modeling, classifying and incrementally learning the QoS ratings.     

Scalable multimedia delivery with QoS management in pervasive computing environment

People are increasingly demanding rich-media and bundled services. However, the diverse terminals, heterogeneous networks as well as various user requirements constrain the multimedia access to low quality in the pervasive computing environment. In order to enable rich-media delivery across a wide range of devices and networks, multimedia adaptation with scalable QoS management is an important issue. Our research introduces a Scalable Multimedia Delivery (SMD) framework with QoS management. This framework utilizes the CAM4Home metadata model to aggregate multimodal rich media services into a bundle. MPEG-21 metadata is integrated into the CAM4Home model to enforce interoperable QoS management. The issues in supporting QoS are addressed on both fidelity and modality. We further develop the SMD system in IP Multimedia Subsystem (IMS) architecture, where multimedia adaptation is implemented through application-level QoS negotiation.     

Optimal adaptation decision-taking for terminal and network quality-of-service

In order to cater to the diversity of terminals and networks, efficient, and flexible adaptation of multimedia content in the delivery path to end consumers is required. To this end, it is necessary to associate the content with metadata that provides the relationship between feasible adaptation choices and various media characteristics obtained as a function of these choices. Furthermore, adaptation is driven by specification of terminal, network, user preference or rights based constraints on media characteristics that are to be satisfied by the adaptation process. Using the metadata and the constraint specification, an adaptation engine can take an appropriate decision for adaptation, efficiently and flexibly. MPEG-21 Part 7 entitled Digital Item Adaptation standardizes among other things the metadata and constraint specifications that act as interfaces to the decision-taking component of an adaptation engine. This paper presents the concepts behind these tools in the standard, shows universal methods based on pattern search to process the information in the tools to make decisions, and presents some adaptation use cases where these tools can be used.     

Quality of service for workflows and web service processes

Workflow management systems (WfMSs) have been used to support various types of business processes for more than a decade now. In workflows or Web processes for e-commerce and Web service applications, suppliers and customers define a binding agreement or contract between the two parties, specifying quality of service (QoS) items such as products or services to be delivered, deadlines, quality of products, and cost of services. The management of QoS metrics directly impacts the success of organizations participating in e-commerce. Therefore, when services or products are created or managed using workflows or Web processes, the underlying workflow engine must accept the specifications and be able to estimate, monitor, and control the QoS rendered to customers. In this paper, we present a predictive QoS model that makes it possible to compute the quality of service for workflows automatically based on atomic task QoS attributes. We also present the implementation of our QoS model for the METEOR workflow system. We describe the components that have been changed or added, and discuss how they interact to enable the management of QoS.     

Application-level QoS control for video-on-demand

User requirements and device heterogeneity call for Web services with differentiated quality of service (QoS). In particular, services with response-time constraints, such as video-on-demand (VoD), require the differentiation, control, and dynamic adaptation of QoS. Service providers and network operators need methodologies and mechanisms for managing runtime QoS. Using mobile agent technology, the ubiQoS middleware supports QoS tailoring and adaptation of video-on-demand flows in response to user preferences and terminal properties. The design, implementation, and deployment of QoS-aware Internet services can significantly benefit from a middleware approach at the application level. Our experimental results show the feasibility of application-level middleware solutions based on code mobility for Internet VoD services with differentiated QoS.     

A new QoS ontology and its QoS-based ranking algorithm for Web services

Web service composition is a promising solution for building distributed applications on the Internet in which Web service discovery is a key step. With a number of Web services having similar functionality, it is necessary to rank those services to select the best Web services for a request. QoS information which can reflect user’s expectation and experience of using a service is often used as a distinguish factor in a service ranking algorithm. Different service providers and participants may use different QoS concepts for describing service quality information. Therefore, it leads to the issue of semantic interoperability of QoS. In this paper, we propose a novel approach for designing and developing a QoS ontology and its QoS-based ranking algorithm for evaluating Web services. The QoS ontology can support not only describing QoS information in great detail but also facilitating various service participants expressing their QoS offers and demands at different levels of expectation. The QoS-based ranking algorithm adopted Analytic Hierarchy Process (AHP), a multiple criteria decision making technique, as an underlying mechanism for developing a flexible and dynamic ranking algorithm. The proposed QoS ontology and ranking algorithm can be used in various applications in order to facilitate automatic and dynamic discovery and selection of Web services.     

Adaptive Quality of Service Support for Packet-Switched Wireless Cellular Networks

In this paper, we propose an adaptive quality of service (QoS) design approach via resource reservation and rate adaptation to support multimedia over wireless cellular networks. Three contributions of this work are: (a) an adaptive QoS model that seeks to provide QoS assurances within bounds for each packet flow and to make advance resource reservation in order to support seamless mobility, (b) a revenue-based resource adaptation design that seeks to maximize network revenue while satisfying the QoS requirements, and (c) a resource reservation protocol that supports both application-initiated resource reservation and network-initiated resource adaptation. Our initial implementation and measurements confirm the effectiveness of the proposed design.     

考虑QoS偏好的多属性群决策服务选择策略

面对多个功能相同或相似的服务,服务的Qo S是服务选择中重要的考虑因素.将Qo S属性分为精确数型、区间数型和三角模糊数型.在此基础上,利用TOPSIS（technique for order preference by similarity to an ideal solution）条件下的多属性群决策模型给出了服务选择过程,该过程考虑了多个决策者在决策过程中所占的权重,以及多个决策者不同的Qo S偏好权重.通过一个实例验证了该方法的有效性.     

Flow-level QoS for a dynamic load of rate adaptive sessions sharing a bottleneck link

We consider the flow-level quality of service (QoS) seen by a dynamic load of rate adaptive sessions sharing a bottleneck link based on fair share bandwidth allocation. This is of interest both in considering wired networks supporting rate adaptive multimedia sessions and wireless networks supporting voice with rate adaptation to realize graceful degradation during congested periods. Two QoS metrics are considered: the time-average instantaneous utility of the allocated bandwidth, and the time-average of transition penalties associated with the changes in allocation seen by a flow. We present a simple model for rate adaptation, where (heterogeneous) flows can vary their rates within (different) ranges, and present closed-form results for these perceived flow-level QoS metrics. We then prove asymptotic results for large capacity systems exhibiting the salient features of rate adaptation in a dynamic network. Finally, we provide a concrete example, showing how the QoS seen by sessions with different degrees of adaptivity would vary under a natural fair bandwidth allocation policy.     

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 framework; 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.     

一种基于QoS的自主通信最优判决策略

论述自主通信的基本组成和功能,将自主通信系统看成一个由采集、分析、判决和动作行为4个单元组成的特殊反馈控制系统,着重分析判决单元。基于QoS研究一种多控制变量、多观测变量马尔可夫最优判决策略。仿真结果表明,采用马尔可夫最优判决策略可以提高系统自适应网络环境变化的能力。     

网格市场中一种模糊决策的多维QoS批调度方法

网格市场环境下,用户的服务质量(QoS)需求更加多样化;更多普通用户加入网格市场,难以提供精确的QoS需求信息.因此,基于用户模糊QoS需求的调度算法成为网格市场中研究的热点.多维QoS网格调度的形式化描述,利用模糊决策理论有效地将用户模糊的QoS需求的映射到网格资源,利用AHP算法确定用户关于多维QoS各维度之间的权重关系,给出一种模糊决策的多维QoS的调度方法.实验表明,模糊决策的多维QoS批调度算法在不需要用户提供精确的QoS参数前提下,有效满足用户QoS需求.与现有的QoS批调度方法相比,该算法具有较好的一次作业完成率,且作业完成率波动较小.     

End-to-end support for statistical quality of service in heterogeneous mobile ad hoc networks

In heterogeneous mobile ad hoc networks (MANETs), different types of mobile devices with diverse capabilities may coexist in the same network. The heterogeneity of MANETs makes end-to-end support for quality of service (QoS) guarantees more difficult than in other types of networks, not to mention the limited bandwidth and frequent topology changes of these networks. Since QoS routing is the first step toward achieving end-to-end QoS guarantees in heterogeneous MANETs, we propose a QoS routing protocol for heterogeneous MANETs. The proposed protocol, called virtual grid architecture protocol (VGAP), uses a cross-layer approach in order to provide end-to-end statistical QoS guarantees. VGAP operates on a fixed virtual rectilinear architecture (virtual grid), which is obtained using location information obtained from global positioning system (GPS). The virtual grid consists of a few, but possibly more powerful, mobile nodes known as ClusterHeads (CHs) that are elected periodically. CHs discover multiple QoS routes on the virtual grid using an extended version of the open shortest path first (OSPF) routing protocol and an extended version of WFQ scheduling policy that takes into account the wireless channel state. Moreover, VGAP utilizes a simple power control algorithm at the physical layer that provides efficient energy savings in this heterogeneous setting. Simulation experiments show that VGAP has a good performance in terms of packet delivery ratio, end-to-end packet delay, call blocking probability, and network scalability.     

QoS Control Strategies for High-Quality Video Processing

Video processing in software is often characterized by highly fluctuating, content-dependent processing times, and a limited tolerance for deadline misses. We present an approach that allows close-to-average-case resource allocation to a single video processing task, based on asynchronous, scalable processing, and QoS adaptation. The QoS adaptation balances different QoS parameters that can be tuned, based on user-perception experiments: picture quality, deadline misses, and quality changes. We model the balancing problem as a discrete stochastic decision problem, and propose two solution strategies, based on a Markov decision process and reinforcement learning, respectively. We enhance both strategies with a compensation for structural (non-stochastic) load fluctuations. Finally, we validate our approach by means of simulation experiments, and conclude that both enhanced strategies perform close to the theoretical optimum.Clemens Wüst received the M.Sc. degree in mathematics with honors from the University of Groningen, The Netherlands. Since then, he has been with the Philips Research Laboratories in Eindhoven, The Netherlands, where he has been working mainly on QoS for resource-constrained real-time systems using stochastic optimization techniques. Currently, he is pursuing a Ph.D. degree at the Technische Universiteit Eindhoven.Liesbeth Steffens received her M.Sc. from Utrecht University (NL) in 1972. She spent most of her professional life in Philips Research in Eindhoven. She contributed to the design of a real-time distributed operating system, a video-on-demand server, a DVD player, a set-top box, and a QoS-based Resource-Management framework for streaming video. Her current focus is on characterization of resource requirements, resource reservation, and system-on-chip infrastructure.Wim F. J. Verhaegh received the mathematical engineering degree with honors in 1990 from the Technische Universiteit Eindhoven, The Netherlands. Since then, he is with the Philips Research Laboratories in Eindhoven, The Netherlands. From 1990 until 1998, he has been a member of the department Digital VLSI, where he has been working on high-level synthesis of DSP systems for video applications, with the emphasis on scheduling problems and techniques. Based on this work, he received a Ph.D. degree in 1995 from the Technische Universiteit Eindhoven. Since 1998, he is working on various optimization aspects of multimedia systems, networks, and applications. On the one hand, this concerns application-level resource management and scheduling, for optimization of quality of service of multimedia systems. On the other hand, this concerns adaptive algorithms and machine learning algorithms for user interaction issues, such as content filtering and automatic playlist generation.Reinder J. Bril received a B.Sc. and a M.Sc. (both with honors) from the Department of Electrical Engineering of the University of Twente, and a Ph.D. from the Technische Universiteit Eindhoven (TU/e), The Netherlands. He started his professional career at the Delft University of technology in the Department of Electrical Engineering. From May 1985 till August 2004, he has been with Philips. He has worked in both Philips Research as well as Philips Business Units, on various topics, including fault-tolerance, formal specifications, and software architecture analysis, and in different application domains. The last five years, he worked at Philips Research Laboratories Eindhoven (PRLE), the Netherlands, in the area of Quality of Service (QoS) for consumer devices, with a focus on dynamic resource management in receivers in broadcast environments (such as digital TV-sets and set-top boxes). In September 2004, he made a transfer to the Technische Universiteit Eindhoven (TU/e), Department of Mathematics and Computer Science, Group System Architecture and Networking (SAN), i.e. back to the academic world, after 19 years in industry.Christian Hentschel received his Dr.-Ing. (Ph.D.) in 1989 and Dr.-Ing. habil. in 1996 at the University of Technology in Braunschweig, Germany. He worked on digital video signal processing with focus on quality improvement. In 1995, he joined Philips Research in Briarcliff Manor, USA, where he headed a research project on moiré analysis and suppression for CRT based displays. In 1997, he moved to Philips Research in Eindhoven, The Netherlands, leading a cluster for Programmable Video Architectures. Later he held a position of a Principal Scientist and coordinated a project on scalable media processing with dynamic resource control between different research laboratories. In 2003, he became a full professor at the Brandenburg University of Technology in Cottbus, Germany. Currently he chairs the department of Media Technology. He is a member of the Technical Committee of the International Conference on Consumer Electronics (IEEE) and a member of the FKTG in Germany.