Two approaches for an adaptive multimedia transfer service for mobile environments

Mobile environments are characterized by varying locations and network access points of end users, by varying levels of network QoS and often also by limited connectivity and reliability. These aspects have to be considered specifically for distributed multimedia applications, typically involving large amounts of data and specific QoS requirements. This article presents concepts and experiences concerning adaptive services for asynchronous multimedia transmission in mobile environments. We describe two different approaches to solve the problems of adaptation to variable network QoS using generic mechanisms. The first approach takes advantage of a mobile queuing service and is based on our former work on a support platform for mobile computing (see Schill and Kümmel. Mobile Computing Special Issue of Distributed Systems Engineering Journal 1995; 128–41; Schill et al. Proceedings of IMC 96 Workshop on Information Visualization and Mobile Computing. Zentrum für graphische Datenverarbeitung, February 1996). The second approach uses the mobile agent paradigm in the context of an application partitioning model to gain flexibility and maintainability (see Schill et al. In: Papaioannou, Minar, editors, Proceedings. Mobile Agents in the Context of Competition and Cooperation (MAC3), a workshop at Autonomous Agents '99, 1999. p. 34–41.). Both approaches exploit software-based conversion to adapt multimedia data according to bandwidth availability. Decoupling of communication peers with automatic notifications about communication actions helps to address disconnection problems.     

基于SOM神经网络的服务质量预测

服务质量预测在服务计算领域中是一个热点研究问题.在历史QoS数据稀疏的情况下,设计一个满足用户个性化需求的服务质量预测方法成为一项挑战.为解决这一挑战问题,本文提出一种基于SOM神经网络的服务质量预测方法SOMQP.首先,基于历史QoS数据,应用SOM神经网络算法分别对用户和服务进行聚类,得到用户关系矩阵和服务关系矩阵;进而,综合考虑用户信誉和服务关联性,采用一种新的Top-k选择机制获得相似用户和相似服务;最后,采用基于用户的和基于项目的混合策略对缺失QoS值进行预测.在真实的数据集WS-Dream上进行大量实验,结果表明,与经典的CF算法和K-means算法相比,本文方法较大程度上提高了QoS预测精度.     

A trustworthy QoS-based collaborative filtering approach for web service discovery

Many network services which process a large quantity of data and knowledge are available in the distributed network environment, and provide applications to users based on Service-Oriented Architecture (SOA) and Web services technology. Therefore, a useful web service discovery approach for data and knowledge discovery process in the complex network environment is a very significant issue. Using the traditional keyword-based search method, users find it difficult to choose the best web services from those with similar functionalities. In addition, in an untrustworthy real world environment, the QoS-based service discovery approach cannot verify the correctness of the web services’ Quality of Service (QoS) values, since such values guaranteed by a service provider are different from the real ones. This work proposes a trustworthy two-phase web service discovery mechanism based on QoS and collaborative filtering, which discovers and recommends the needed web services effectively for users in the distributed environment, and also solves the problem of services with incorrect QoS information. In the experiment, the theoretical analysis and simulation experiment results show that the proposed method can accurately recommend the needed services to users, and improve the recommendation quality.     

Developing a navigation aid for the frail and visually impaired

This paper describes the development of a new navigational aid for the frail, elderly, and visually impaired person. The users were involved both in the user requirements study and in the evaluation of different prototypes. The results show that the users were able to provide information on their current aid, the use situation, and their preference regarding different solutions, but they had difficulties to provide the detailed answers on technical solutions required by the technical development team. Further, prototype evaluations with users enabled the technical team to understand the users and their use situation.     

考虑数据安全的工业互联网制造服务QoS多方联合预测

工业互联网平台支持各类制造资源的泛在连接,能够为不同用户提供全生命周期的制造服务。制造服务QoS（quality of service）在服务匹配、选择和共享中扮演重要角色。然而,如何在保护数据安全的前提下充分利用工业互联网平台下不同企业的制造服务特征数据,对提高QoS预测精度至关重要。为此,提出了一种QoS多方联合预测方法。首先,根据各制造服务商在本地长期累计的相关数据,建立用户—制造服务QoS关系矩阵;进而,在保护用户偏好信息安全下共享企业间制造服务的潜在特征向量实现QoS联合训练,同时应用同态加密与差分隐私加密机制保证传输数据的安全;最后,应用随机梯度下降法迭代更新模型参数以预测缺失的制造服务QoS值。实验以WS-dream数据集与案例企业制造服务共享平台数据为例验证了该方法的有效性,结果表明该方法能够在保护数据安全的前提下,有效地提高模型预测的准确度。     

Multi-user web service selection based on multi-QoS prediction

In order to find best services to meet multi-user’s QoS requirements, some multi-user Web service selection schemes were proposed. However, the unavoidable challenges in these schemes are the efficiency and effect. Most existing schemes are proposed for the single request condition without considering the overload of Web services, which cannot be directly used in this problem. Furthermore, existing methods assumed the QoS information for users are all known and accurate, and in real case, there are always many missing QoS values in history records, which increase the difficulty of the selection. In this paper, we propose a new framework for multi-user Web service selection problem. This framework first predicts the missing multi-QoS values according to the historical QoS experience from users, and then selects the global optimal solution for multi-user by our fast match approach. Comprehensive empirical studies demonstrate the utility of the proposed method.     

Optimizing security and quality of service in a Real-time database system using Multi-objective genetic algorithm

Both network security and quality of service (QoS) consume computational resource of IT system and thus may evidently affect the application services. In the case of limited computational resource, it is important to model the mutual influence between network security and QoS, which can be concurrently optimized in order to provide a better performance under the available computational resource. In this paper, an evaluation model is accordingly presented to describe the mutual influence of network security and QoS, and then a multi-objective genetic algorithm NSGA-II is revised to optimize the multi-objective model. Using the intrinsic information from the target problem, a new crossover approach is designed to further enhance the optimization performance. Simulation results validate that our algorithm can find a set of Pareto-optimal security policies under different network workloads, which can be provided to the potential users as the differentiated security preferences. These obtained Pareto-optimal security policies not only meet the security requirement of the user, but also provide the optimal QoS under the available computational resource.     

Efficient and reliable service selection for heterogeneous distributed software systems

The service-oriented paradigm is emerging as a new approach to heterogeneous distributed software systems composed of services accessed locally or remotely by middleware technology. How to select the optimal composited service from a set of functionally equivalent services with different quality of service (QoS) attributes has become an active focus of research in the service community. However, existing middleware solutions or approaches are inefficient as they search all solution spaces. More importantly, they inherently neglect QoS uncertainty owing to the dynamic network environment. In this paper, based on a service composition middleware framework, we propose an efficient and reliable service selection approach that attempts to select the best reliable composited service by filtering low-reliability services through the computation of QoS uncertainty. The approach first employs information theory and probability theory to abandon high-QoS-uncertainty services and downsize the solution space. A reliability fitness function is then designed to select the best reliable service for composited services. We experimented with real-world and synthetic datasets and compared our approach with other approaches. Our results show that our approach is not only fast, but also finds more reliable composited services.     

一种基于用户情境的QoS预测方法

完整的QoS信息有利于更准确的服务推荐,但是现实中往往很难得到。文章提出了一种基于用户情境的QoS预测方法,对于老用户,根据他们原来的QoS选择,考虑QoS类型区别和时间衰减情况,预测新的QoS取值;对于新用户,按照用户分类信息,根据同类用户的服务选择情况,预测他们的QoS取值。实验证明,该方法有助于提高服务推荐的性能。     

一种基于QoS的Internet服务管理体系结构

服务定位协议(SLP)是IETF提出的基于IP网络的服务定位标准。而这一标准并没有考虑对QoS的支持。未来的互联网络是一个具有QoS保证的网络。服务发现仅仅是Internet服务管理中的一个方面，发现服务不是最终目的，最终目的是为了使用这一服务。在对SLP体系结构、下一代互联网QoS服务管理及相关技术充分研究的基础上，提出了一种新奇的基于QoS的Internet服务管理体系结构模型。为使在服务表示与发现层支持QoS，对SLP定位协议进行了一些扩充。对服务定位协议扩充后，当用户代理在向服务代理发布请求时，可以在请求消息中绑定QoS对象参数，一旦服务代理接收到这一消息，就可以利用这些QoS参数与域管理器进行协商，协商结果可通过服务代理反馈给用户代理。这样不仅减小了网络开销，而且降低了传统的用户代理与域管理器协商的次数，在服务发现的同时用户代理还可以直接获得该服务的QoS信息。     

A multimedia service composition scheme for ubiquitous networks

It is a challenging task to develop a high quality and secure multimedia service for mobile terminals used in the ubiquitous computing environment. One of the issues is the resource limitation of mobile terminals. In this paper, we presented a multimedia service composition scheme for sharing computer and communication resources by using plural terminals to compensate for this resource limitation. The proposed scheme is based on user authentication, service access control, and the multi-agent-based adaptive Quality-of-Service (QoS) control framework that we developed. We also proposed a novel access mode control based on the trustworthiness of users and extension of the multi-agent-based adaptive QoS control framework to plural users. Focusing on the home network as a typical ubiquitous network, we implemented a prototype testbed system and showed experimental results for the multimedia service composition.     

QoS Driven Per-Request Load-Aware Service Selection in Service Oriented Architectures

Service selection has been widely investigated by the SOA research community as an effective adaptation mechanism that allows a service broker, offering a composite service, to bind at runtime each task of the composite service to a corresponding concrete implementation, selecting it from a set of candidates which differ from one another in terms of QoS parameters. In this paper we present a load-aware per-request approach to service selection which aims to combine the relative benefits of the well known per-request and perflow approaches. Our service selection policy represents the core methodology of the Plan phase of a self-adaptive service oriented system based on the MAPE-K reference loop. Since the service broker operates in a variable and uncertain environment where the QoS levels negotiated with the service providers can fluctuate, it requires some mechanism to enforce the QoS constraints with its users. To this end, we also propose an algorithm for the Analyze phase of MAPE-K which is based on the adaptive Cusum algorithm and allows to determine whether a change in the QoS level requires a service selection replanning. We present experimental results obtained with a prototype implementation of a service broker. Our results show that the proposed load-aware approach is superior to the traditional perrequest one and combines the ability of sustaining large volume of service requests, as the perflow approach, while at the same time offering a finer customizable service selection, as the per-request approach. Furthermore, the results show that the adaptive Cusum algorithm can quickly detect changes in the execution environment and trigger a new optimization plan before the system performance degrades.     

CluCF: a clustering CF algorithm to address data sparsity problem

In QoS-based Web service recommendation, predicting Quality of Service (QoS) for users will greatly aid service selection and discovery. Collaborative filtering (CF) is an effective method for Web service selection and recommendation. Data sparsity is an important challenges for CF algorithms. Although model-based algorithms can address the data sparsity problem, those models are often time-consuming to build and update. Thus, these CF algorithms aren’t fit for highly dynamic and large-scale environments, such as Web service recommendation systems. In order to overcome this drawback, this paper proposes a novel approach CluCF, which employs user clusters and service clusters to address the data sparsity problem and classifies the new user (the new service) by location factor to lower the time complexity of updating clusters. Additionally, in order to improve the prediction accuracy, CluCF employs time factor. Time-aware user-service matrix Mu;s(tk, d) is introduced, and the time-aware similarity measurement and time-aware QoS prediction are employed in this paper. Since the QoS performance of Web services is highly related to invocation time due to some time-varying factors (e.g., service status, network condition), time-aware similarity measurement and time-aware QoS prediction are more trustworthy than traditional similarity measurement and QoS prediction, respectively. Since similarity measurement and QoS prediction are two key steps of neighborhood-based CF, time-aware CF will be more accurate than traditional CF. Moreover, our approach systematically combines user-based and item-based methods and employs influence weights to balance these two predicted values, automatically. To validate our algorithm, this paper conducts a series of large-scale experiments based on a real-world Web service QoS dataset. Experimental results show that our approach is capable of alleviating the data sparsity problem.     

多元时间序列的Web Service QoS预测方法

为准确并多步预测Web服务的服务质量（quality of service,简称QoS）,方便用户选择更好的Web服务,提出了一种基于多元时间序列的QoS预测方法MulA-LMRBF （multiple step forecasting with advertisement-levenberg marquardt radial basis function）.充分考虑多个QoS属性序列之间的关联,采用平均位移法（average dimension,简称AD）确定相空间重构的嵌入维数和延迟时间,将QoS属性历史数据映射到一个动力系统中,近似恢复多个QoS属性之间的多维非线性关系.将短期服务提供商QoS广告数据加入数据集中,采用列文伯格-马夸尔特法（Levenberg-Marquardt,简称LM）算法改进的径向基（radial basis function,简称RBF）神经网络预测模型,动态更新神经网络的权重,提高预测精度,实现QoS动态多步预测.通过网络开源数据和自测数据的实验结果表明,该方法与传统方法相比有较好预测效果,更适合动态多步预测.     

Performance measurement for parallel and distributed programs: astructured and automatic approach

Novel approaches are presented for designing performance measurement systems for parallel and distributed programs. The first approach involves unifying performance information into a single, regular structure that reflects the structure of programs under measurement. The authors define a hierarchical model for the execution of parallel and distributed programs as a framework for the performance measurement. A complete different levels of detail in the hierarchy. The second approach is based on the development of automatic guidance techniques that can direct users to the location of performance problems in the program. Guidance information from such techniques supplies facts about problems in the program and provides possible answers for the further improvement of program efficiency. A performance measurement system, called IPS, has been developed as a prototype of the authors' model and design. Some of the test results from IPS are also discussed     

A new approach to dynamic bandwidth allocation in Quality of Service networks: Performance and bounds

Efficient dynamic resource provisioning algorithms are necessary to the development and automation of Quality of Service (QoS) networks. The main goal of these algorithms is to offer services that satisfy the QoS requirements of individual users while guaranteeing at the same time an efficient utilization of network resources.In this paper we introduce a new service model that provides per-flow bandwidth guarantees, where users subscribe for a guaranteed rate; moreover, the network periodically individuates unused bandwidth and proposes short-term contracts where extra-bandwidth is allocated and guaranteed exclusively to users who can exploit it to transmit at a rate higher than their subscribed rate.To implement this service model we propose a dynamic provisioning architecture for intra-domain Quality of Service networks. We develop a set of dynamic on-line bandwidth allocation algorithms that take explicitly into account traffic statistics and users’ utility functions to increase users’ benefit and network revenue.Further, we propose a mathematical formulation of the extra-bandwidth allocation problem that maximizes network revenue. The solution of this model allows to obtain an upper bound on the performance achievable by any on-line bandwidth allocation algorithm.We demonstrate through simulation in realistic network scenarios that the proposed dynamic allocation algorithms are superior to static provisioning in providing resource allocation both in terms of total accepted load and network revenue, and they approach, in several network scenarios, the ideal performance provided by the mathematical model.     

QoS prediction for web services based on user-trust propagation model

There is an important online role for Web service providers and users; however, the rapidly growing number of service providers and users, it can create some similar functions among web services. This is an exciting area for research, and researchers seek to to propose solutions for the best service to users. Collaborative filtering (CF) algorithms are widely used in recommendation systems, although these are less effective for cold-start users. Recently, some recommender systems have been developed based on social network models, and the results show that social network models have better performance in terms of CF, especially for cold-start users. However, most social network-based recommendations do not consider the user’s mood. This is a hidden source of information, and is very useful in improving prediction efficiency. In this paper, we introduce a new model called User-Trust Propagation (UTP). The model uses a combination of trust and the mood of users to predict the QoS value and matrix factorisation (MF), which is used to train the model. The experimental results show that the proposed model gives better accuracy than other models, especially for the cold-start problem.     

基于时间感知排序的云服务QoS预测方法研究

随着云计算理论和技术的成熟,越来越多的云服务得到了蓬勃发展,如何建立高质量的云服务成为了云计算研究领域的一个关键难题。服务质量QoS排序为用户从一系列功能相似的云服务候选者中挑选最优云服务提供了非常有价值的信息。为了获得云服务的QoS值,就需要调用真实的候选云服务。为了避免时间消耗和昂贵的资源浪费,提出了一种基于时间感知排序的云服务QoS预测方法。不同于传统的QoS值预测,基于QoS排序相似度的预测考虑为特定用户检测服务的排序。分时段按权计算出排序相似度,结合时间偏好合成相似度的前k位用户,用来提供信息支持QoS的缺失预测。在WS Dream真实数据集进行的实验研究表明,基于时间感知排序的云服务QoS预测方法有更好的预测精度。     

一种基于多Agent服务的网络体系结构

本文从 Ａ Ｔ Ｍ 模型出发,介绍了一种基于多 Ａｇｅｎｔ服务的网络体系结构。本结构在硬软件方面提供通信服务、链接许可控制及信令服务等功能;支持以用户为中心的 Ｑｏ Ｓ 规程,允许多 Ａｇｅｎｔ 满足终端用户的各种服务请求。本结构之原型模拟系统经运行后,初步实现了内部带宽存储等机制,有效地满足了用户的 Ｑｏ Ｓ需求。     

A framework based approach to the development of network awareapplications

Modern networks provide a QoS (quality of service) model to go beyond best-effort services, but current QoS models are oriented towards low-level network parameters (e.g., bandwidth, latency, jitter). Application developers, on the other hand, are interested in quality models that are meaningful to the end-user and, therefore, struggle to bridge the gap between network and application QoS models. Examples of application quality models are response time, predictability or a budget (for transmission costs). Applications that can deal with changes in the network environment are called network-aware. A network-aware application attempts to adjust its resource demands in response to network performance variations. This paper presents a framework-based approach to the construction of network-aware programs. At the core of the framework is a feedback loop that controls the adjustment of the application to network properties. The framework provides the skeleton to address two fundamental challenges for the construction of network-aware applications: how to find out about dynamic changes in network service quality; and how to map application-centric quality measures (e.g., predictability) to network-centric quality measures (e.g., QoS models that focus on bandwidth or latency). Our preliminary experience with a prototype network-aware image retrieval system demonstrates the feasibility of our approach. The prototype illustrates that there is more to network-awareness than just taking network resources and protocols into account and raises questions that need to be addressed (from a software engineering point of view) to make a general approach to network-aware applications useful