Towards an ideal service QoS in fuzzy logic-based adaptation planning middleware

Mobile applications require an adaptation phase to adapt to the user's and application context. Utility functions or rules are most often used to make the adaptation planning or decision, i.e. select the most adapted variant for each required service. Fuzzy controllers are used when it is difficult or even impossible to construct precise mathematical models. In the case of mobile applications, the large number of Quality of Service (QoS) and context parameters causes an exponential increase in the number of rules (aka. rule explosion problem), that increases the processing time of the adaptation planning. To reduce the processing time and simplify the fuzzy control system, we propose the concept of ideal QoS. Fuzzy values of ideal QoS parameters are calculated using several fuzzy control systems to fit the context state and user preferences. A fuzzy logic similarity metric based on fuzzy sets and fuzzy operators is proposed to select the service variant having the nearest QoS values to the ideal. Experiments show that our approach can significantly improve both the number of rules and the processing time when selecting the variant that well adapts to environment changes.     

基于反射式中间件的移动计算模型

为解决移动计算环境中服务质量控制问题,提出一种移动服务计算模型.模型包括环境感知层、中间件层和服务器层,使用反射技术在应用程序运行时检查服务器的资源状况,根据预先设定的策略动态地调整系统资源,以适应具体应用的资源需求.实验结果表明,该模型可以使客户端在高负载情况下获得更多的服务器资源,并有效减小服务器端的响应时间.     

基于网格计算的QoS模型的研究

随着网格技术和应用的不断深入，对网格提出了严格的服务质量（quality of service，简称QoS）要求，网格计算中的QoS成为研究应用的焦点．缺乏QoS保证逐渐成为制约网格应用的瓶颈之一。论文对网格计算的质量服务进行了研究，描述了网格QoS定义，网格QoS需求和网格QoS的层次模型。同时也介绍了当前研究思路度以后的发展趋势。     

Tradeoffs between energy consumption and QoS in mobile grid

Mobile grid, which combines grid and mobile computing, supports mobile users and resources in a seamless and transparent way. However, mobility, QoS support, energy management, and service provisioning pose challenges to mobile grid. The paper presents a tradeoff policy between energy consumption and QoS in the mobile grid environment. Utility function is used to specify each QoS dimension; we formulate the problem of energy and QoS tradeoff by utility optimization. The work is different from the classical energy aware scheduling, which usually takes the consumed energy as the constraints; our utility model regards consumed energy as one of the components of measure of the utility values, which indicates the tradeoff of application satisfaction and consumed energy. It is a more accurate utility model for abstracting the energy characteristics and QoS requirement for mobile users and resources in mobile grid. The paper also proposes a distributed energy–QoS tradeoff algorithm. The performance evaluation of our energy–QoS tradeoff algorithm is evaluated and compared with other energy and deadline constrained scheduling algorithm.     

移动自组网QoS路由的DNA计算模型

QoS路由问题是移动自组网应用面临的一个重要问题,其中如何根据移动自组网动态拓扑结构和单向链路的特点来设计路由算法是关键。DNA计算是一种基于生化反应的新型计算方法,高度的并行性和海量存储能力是其最大的特点。文章首先给出了QoS路由问题模型,然后介绍了DNA的分子结构和DNA计算的基本原理,最后依据Adleman进行DNA计算的编码方法,给出了移动自组网QoS路由问题的DNA计算模型,为解决多约束QoS路由问题提供了一种新的思路。     

全IP移动网络基于弱动态资源预留的QoS保证机制

移动性管理和QoS保障机制是全IP移动网络中的两个关键技术。如何将二者结合起来，为用户提供可靠的有保障的服务，无疑是非常重要的问题。针对RSVP不适应移动环境的缺点，结合微移动协议，本文在全IP移动网络接入网的微移动域中，提出一种弱动态资源预留（WDRSVP）的QoS解决方案，实现微移动协议和RSVP协议之间的互操作。仿真证明，我们的方法能够有效地利用资源，能够更好地保证移动节点在切换时的通信服务质量。     

基于CORBA的分布式多媒体服务的QoS模型

对于分布式多媒体来说,必须保证包括端系统、通讯系统以及网络在内的整个系统的服务质量（QoS）。CORBA提供了一个开放式的分布式对象计算环境,它能使许多普通的网络程序设计自动化,并允许应用在异构环境下无缝链接。文章根据分布式多媒体通讯系统中的层次结构模型（QOS－A）,提出了一种基于CORBA的分布式多媒体模型。     

CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms

Cloud computing is a recent advancement wherein IT infrastructure and applications are provided as ‘services’ to end‐users under a usage‐based payment model. It can leverage virtualized services even on the fly based on requirements (workload patterns and QoS) varying with time. The application services hosted under Cloud computing model have complex provisioning, composition, configuration, and deployment requirements. Evaluating the performance of Cloud provisioning policies, application workload models, and resources performance models in a repeatable manner under varying system and user configurations and requirements is difficult to achieve. To overcome this challenge, we propose CloudSim: an extensible simulation toolkit that enables modeling and simulation of Cloud computing systems and application provisioning environments. The CloudSim toolkit supports both system and behavior modeling of Cloud system components such as data centers, virtual machines (VMs) and resource provisioning policies. It implements generic application provisioning techniques that can be extended with ease and limited effort. Currently, it supports modeling and simulation of Cloud computing environments consisting of both single and inter‐networked clouds (federation of clouds). Moreover, it exposes custom interfaces for implementing policies and provisioning techniques for allocation of VMs under inter‐networked Cloud computing scenarios. Several researchers from organizations, such as HP Labs in U.S.A., are using CloudSim in their investigation on Cloud resource provisioning and energy‐efficient management of data center resources. The usefulness of CloudSim is demonstrated by a case study involving dynamic provisioning of application services in the hybrid federated clouds environment. The result of this case study proves that the federated Cloud computing model significantly improves the application QoS requirements under fluctuating resource and service demand patterns. Copyright © 2010 John Wiley & Sons, Ltd.     

QuCOM:一种面向构件系统的QoS管理模型

在性能变化不确定的系统内,不同的应用处于竞争和共享有限的系统资源、并受其变化影响的环境中．在系统运行时,对于需要QoS保证的应用,为保证其QoS属性,应能适应于这种环境．考虑到系统资源的全局管理特性,仅从应用中增加适应机制是不够的,还需在系统层中增加QoS管理机制．为此,给出了一种面向构件系统的QoS管理模型——QuCOM（quality component）及其集成到系统构件框架的方法,使基于QuCOM开发的构件应用能够适应于变化的系统环境,并为了验证QuCOM的有效性,以一个视频流应用为例,给出了相关实验数据分析．     

OnceAS/Q:一个面向QoS的Web应用服务器

网络分布计算环境下应用系统的需求多样化和复杂性的增长,要求位于中间件层次的Web应用服务器(web application server,简称WAS)从原来的"尽力而为"服务模型转变为服务质量(quality of service,简称QoS)保障模型,为具有不同需求的应用分别提供适宜的服务质量保障.目前的WAS系统在此方面仍然比较薄弱.OnceAS/Q是一个面向QoS的WAS系统,它以QoS规约为基础,为不同应用提供不同的QoS保障能力.OnceAS/Q实现了一个应用QoS保障框架,提供了一组QoS服务组件支持具有QoS需求的应用开发和运行.介绍了OnceAS/Q的体系结构和主要组件,详细阐述了两个关键问题,一是QoS规约的定义及其映射,另一个是面向QoS的服务组件和资源的动态重配.OnceAS/Q原型在Ecperf测试基准下,对其QoS保障能力进行了实验.实验数据表明,在较大规模的应用环境下,OnceAS/Q能够提供更好的服务质量,并且开销是可接受的.     

移动计算环境下的QoS技术

QoS管理和控制是移动计算中的一个重要研究领域。该领域的主要研究内容有环境识别、适应性管理、资源管理和资源预留等。本文论述了移动计算环境下QoS研究中的一些基本概念、主要问题、研究内容和方法，并对该领域最近的研究工作进行了综述。     

Autonomic QoS control in enterprise Grid environments using online simulation

As Grid Computing increasingly enters the commercial domain, performance and quality of service (QoS) issues are becoming a major concern. The inherent complexity, heterogeneity and dynamics of Grid computing environments pose some challenges in managing their capacity to ensure that QoS requirements are continuously met. In this paper, a comprehensive framework for autonomic QoS control in enterprise Grid environments using online simulation is proposed. This paper presents a novel methodology for designing autonomic QoS-aware resource managers that have the capability to predict the performance of the Grid components they manage and allocate resources in such a way that service level agreements are honored. Support for advanced features such as autonomic workload characterization on-the-fly, dynamic deployment of Grid servers on demand, as well as dynamic system reconfiguration after a server failure is provided. The goal is to make the Grid middleware self-configurable and adaptable to changes in the system environment and workload. The approach is subjected to an extensive experimental evaluation in the context of a real-world Grid environment and its effectiveness, practicality and performance are demonstrated.     

基于多维QoS的集群作业调度算法

调度技术是集群作业管理系统的关键技术之一。但是,目前大多数集群作业管理系统采用的调度技术,很少按照应用对系统资源的需求加以详细区分和权衡,无法同时满足不同应用在高吞吐量、高可用性和实时性等方面的要求,造成了资源的闲置和资源因为负载过重而无法正常工作。该文正是注意到了这种不足,根据不同应用的需求和实时收集到的资源信息,引入了多维QoS的概念,并给出了多维QoS的数学模型,提出了一种基于多维QoS的集群作业调度算法JSBMQ,充分提高了系统的资源利用率和平均响应时间,使集群可以提供不问断的高效的计算服务。     

一种基于在线反向拍卖技术的计算网格资源分配方法

利用经济模型研究网格资源管理是当前网格研究新的热点。在已有的网格资源管理方法的基础上,针对供大于求的计算网格环境,提出了一种基于在线反向拍卖技术的计算网格资源分配方法,并定义了相应的QoS函数,分析了该方法的适用范围和优点。最后通过模拟实验验证了该方法的效用,实验结果证明该方法是一种有效的计算网格资源分配方法。     

Self-adaptation of mobile systems driven by the Common Variability Language

The execution context in which pervasive systems or mobile computing run changes continually. Hence, applications for these systems require support for self-adaptation to the continual context changes. Most of the approaches for self-adaptive systems implement a reconfiguration service that receives as input the list of all possible configurations and the plans to switch between them. In this paper we present an alternative approach for the automatic generation of application configurations and the reconfiguration plans at runtime. With our approach, the generated configurations are optimal as regards different criteria, such as functionality or resource consumption (e.g. battery or memory). This is achieved by: (1) modelling architectural variability at design-time using the Common Variability Language (CVL), and (2) using a genetic algorithm that finds nearly-optimal configurations at run-time using the information provided by the variability model. We also specify a case study and we use it to evaluate our approach, showing that it is efficient and suitable for devices with scarce resources.     

Dynamic cloud resource management for efficient media applications in mobile computing environments

Single-instruction-set architecture (Single-ISA) heterogeneous multi-core processors (HMP) are superior to Symmetric Multi-core processors in performance per watt. They are popular in many aspects of the Internet of Things, including mobile multimedia cloud computing platforms. One Single-ISA HMP integrates both fast out-of-order cores and slow simpler cores, while all cores are sharing the same ISA. The quality of service (QoS) is most important for virtual machine (VM) resource management in multimedia mobile computing, particularly in Single-ISA heterogeneous multi-core cloud computing platforms. Therefore, in this paper, we propose a dynamic cloud resource management (DCRM) policy to improve the QoS in multimedia mobile computing. DCRM dynamically and optimally partitions shared resources according to service or application requirements. Moreover, DCRM combines resource-aware VM allocation to maximize the effectiveness of the heterogeneous multi-core cloud platform. The basic idea for this performance improvement is to balance the shared resource allocations with these resources requirements. The experimental results show that DCRM behaves better in both response time and QoS, thus proving that DCRM is good at shared resource management in mobile media cloud computing.     

Enhancing Availability of Grid Computational Services to Ubiquitous Computing Applications

The Grid is an integrated infrastructure that can play the dual roles of a coordinated resource consumer as well as a donator in distributed computing environments. The enormous growth in the use of mobile and embedded devices in ubiquitous computing environment and their interaction with human beings produces a huge amount of data that need to be processed efficiently anytime anywhere. However, such devices often have limited resources in terms of CPU, storage, battery power, and communication bandwidth. Thus, there is a need to transfer ubiquitous computing application services to more powerful computational resources. In this paper, we investigate the use of the Grid as a candidate for provisioning computational services to applications in ubiquitous computing environments. In particular, we present a competitive model that describes the possible interaction between the competing resources in the Grid Infrastructure as service providers and ubiquitous applications as subscribers. The competition takes place in terms of quality of service (QoS) and cost offered by different Grid Service Providers (GSPs). We also investigate the job allocation of different GSPs by exploiting the noncooperativeness among the strategies. We present the equilibrium behavior of our model facing global competition under stochastic demand and estimate guaranteed QoS assurance level by efficiently satisfying the requirement of ubiquitous application. We have also performed extensive experiments over Distributed Parallel Computing Cluster (DPCC) and studied overall job execution performance of different GSPs under a wide range of QoS parameters using different strategies. Our model and performance evaluation results can serve as a valuable reference for designing appropriate strategies in a practical grid environment.     

QoS-Aware Admission Control and Dynamic Resource Provisioning Framework in Ubiquitous Multimedia Computing Environments

A ubiquitous service deployment is emerging in the multimedia, networking, and wireless mobile computing area. Therefore, there has been an increasing demand for ubiquitous computing environments to support a certain degree of quality of service (QoS) to meet various service requirements from different computing and networking applications, and to better utilize the computing resources. However, supporting QoS in the ubiquitous computing environments has also raised great concerns regarding the applicability of any QoS solution. Management of such ubiquitous multimedia applications requires new mechanisms, i.e., Soft-QoS framework, to be developed for admission control, negotiation, allocation, and scheduling. In this paper, we present a novel negotiated admission control algorithm that exploits the degradability property of applications to improve the performance of the system. The algorithm is based on setting aside a portion of the resources as reserves and managing it intelligently, so that the total utility of the system can be maximized. The mixed greedy and predictive strategy leads to an efficient protocol that also improves the system performance. We use the constructs of application benefit functions and resource demand functions in the integrated admission control and negotiation protocol. We applied our Soft-QoS framework to the admission controlling and resource scheduling for ubiquitous multimedia devices such as Continuous Media (CM) or Video-On-Demand (VOD) servers, where multimedia applications can generally tolerate certain variations on QoS parameters by providing multiple classes with consistently proportional rather than absolute QoS. Extensive simulation experiments are presented in the paper to evaluate the performance of the novel mechanisms and compare it against some other methods used in the past.This work was in part funded by DARPA through the SPAWARSYSCEN under Contract Number N66001-97-C-8525 and SK Telecom, Korea, under Contract Number (KU-R0405721).     

普适计算环境中上下文模型的建立

普适计算作为第三代计算方式已经成为科学研究的前沿,上下文作为普适计算中最为重要研究方向之一,对普适计算的研究和发展有着大力地推动作用.就建立普适计算环境上下文模型进行了分析和讨论,对上下文的数据和通信方式也进行了分析,为上下文的实际应用提供一些理论基础准备.     

Dynamic QoS Adaptation for Mobile Middleware

Computation and networking resources in mobile operating environments are much scarcer and more dynamic than in desktop operating environments. Mobile applications can leverage on the benefits of adaptive computing to optimize the QoS delivery based on contextual situations. Fuzzy control models have been successfully applied to various distributed network QoS management systems. However, existing models are either application-specific or limited to abstract modeling and simple conceptual scenarios which do not take into account overall model scalability. Specifically, the large number of QoS parameters in a mobile operating environment causes an exponential increase in the number of rules correspondingly increases the demand for processing power to infer the rules. Hierarchical fuzzy systems were introduced to reduce the number of rules using hierarchical fuzzy control, in which correlated linguistic variables are hierarchically inferred and grouped into abstract linguistic variables. In this paper, we propose a mobile QoS management framework that uses a hierarchical fuzzy control model to support a highly extensible and structured adaptation paradigm. The proposed framework integrates several levels of QoS abstractions derived from user-perceived requirements.