SLA-Driven Clustering of QoS-Aware Application Servers

In this paper, we discuss the design, implementation, and experimental evaluation of a middleware architecture for enabling service level agreement (SLA)-driven clustering of QoS-aware application servers. Our middleware architecture supports application server technologies with dynamic resource management: application servers can dynamically change the amount of clustered resources assigned to hosted applications on-demand so as to meet application-level quality of service (QoS) requirements. These requirements can include timeliness, availability, and high throughput and are specified in SLAs. A prototype of our architecture has been implemented using the open-source J2EE application server JBoss. The evaluation of this prototype shows that our approach makes possible JBoss' resource usage optimization and allows JBoss to effectively meet the QoS requirements of the applications it hosts, i.e., to honor the SLAs of those applications     

多级实时数据库的安全性策略

实时数据库根本目标就是使满足截止时间的事物数量为最大,因而,管理和支持优先考虑时间的事务处理是非常重要的。然而,随着实时计算的迅速发展,安全成了许多实时应用另一个必须考虑的问题。因此,在多级实时数据库系统中,提出一种结合实时性和安全性的方法是非常必要的。本文陈述了实时系统设计者应该考虑的实时性和安全性,描述了一种规范语言允许设计者在适当的级别设定数据库的重要属性以支持部分安全并探讨了一种自适应方法以达此目的。     

Managing deadline miss ratio and sensor data freshness in real-time databases

The demand for real-time data services is increasing in many applications including e-commerce, agile manufacturing, and telecommunications network management. In these applications, it is desirable to execute transactions within their deadlines, i.e., before the real-world status changes, using fresh (temporally consistent) data. However, meeting these fundamental requirements is challenging due to dynamic workloads and data access patterns in these applications. Further, transaction timeliness and data freshness requirements may conflict. We define average/transient deadline miss ratio and new data freshness metrics to let a database administrator specify the desired quality of real-time data services for a specific application. We also present a novel QoS management architecture for real-time databases to support the desired QoS even in the presence of unpredictable workloads and access patterns. To prevent overload and support the desired QoS, the presented architecture applies feedback control, admission control, and flexible freshness management schemes. A simulation study shows that our QoS-aware approach can achieve a near zero miss ratio and perfect freshness, meeting basic requirements for real-time transaction processing. In contrast, baseline approaches fail to support the desired miss ratio and/or freshness in the presence of unpredictable workloads and data access patterns.     

Multi-constraints self-adaptation for reconfigurable multimedia embedded systems

The application of multimedia in embedded systems (ES), such as Virtual reality and 3-D imaging, represents the current trend in ES development. Coupling multimedia with ES has raised new multimedia-related challenges that have been added to the common ES constraints. These challenges deal with the real-time, quality, performance and efficient processing requirements of multimedia applications. The integration of self-adaptation in ES development has been, for many years, a paramount solution to cope with these issues. Although there has been extensive research on the topic of ES self-adaptation, the related works still lack global approaches that better deal with multimedia-related constraints. Coordinating different adaptation mechanisms, monitoring multiple system constraints and supporting multi-application contexts are still underexplored. The aim of the present work is to fill in these gaps by providing a global adaptation approach that offers better adaptation decisions with fair resource sharing among competing multimedia applications. With the above challenges in mind, we propose a multi-constraints combined adaptation approach that targets multimedia ES. It addresses four critical system constraints: maximizing the overall system‘s Quality of Application (QoA) under the real-time constraint, the remaining system energy and the available network bandwidth. It coordinates the adaptation at both application and architecture levels. To test and validate the proposed technique, a videophone system is designed on a Xilinx FPGA development board. It executes two complex multimedia applications. The validation results show the aptitude of the proposed system to successfully reconfigure itself at run-time in response to its constraints.

     

Decentralized resource management for a distributed continuous media server

Distributed continuous media server (DCMS) architectures are proposed to minimize the communication-storage cost for those continuous media applications that serve a large number of geographically distributed clients. Typically, a DCMS is designed as a pure hierarchy (tree) of centralized continuous media servers. In an earlier work, we proposed a redundant hierarchical topology for DCMS networks, termed RedHi, which can potentially result in higher utilization and better reliability over pure hierarchy. We focus on the design of a resource management system for RedHi that can exploit the resources of its DCMS network to achieve these performance objectives. Our proposed resource management system is based on a fully decentralized approach to achieve optimal scalability and robustness. In general, the major drawback of a fully decentralized design is the increase in latency time and communication overhead to locate the requested object. However, as compared to the typically long duration and high resource/bandwidth requirements of continuous media objects, the extra latency and overhead of a decentralized resource management approach become negligible. Moreover, our resource management system collapses three management tasks: (1) object location, (2) path selection, and (3) resource reservation, into one fully decentralized object delivery mechanism, reducing the latency even further. In sum, decentralization of the resource management satisfies our scalability and robustness objectives, whereas collapsing the management tasks helps alleviate the latency and overhead constraints.     

一种面向云多层应用的费用高效的资源管理方法

由于部署方便、维护简单并且不需要搭建自己的私有机房,云数据中心正成为大多数互联网公司 尤其是初创公司和中小规模公司 部署应用程序的首选。在以基础设施为服务的云环境里,互联网公司可以根据应用程序的需要动态租赁云基础设施,从而节省预算开支,并保证应用性能。然而,在现有的业界实践中,云服务提供商提供的负载均衡和资源伸缩服务只能监控虚拟机的使用状态,并不能监控应用程序的运行状态,因此无法准确根据应用程序的服务需求自适应变换资源规模。同时,现有的文献和实践中,也很少有 研究从云基础设施使用者的角度出发,为使用者节省基础设施租赁费用或高效使用已租赁基础设施。据此提出了一种面向基础设施云环境下多层应用的费用高效的资源管理方法,其在降低用户费用的同时,还能充分利用所花费用提高应用程序性能。通过仿真对所提方法业界实际使用的方法 进行比较,结果表明所提方法不仅能够提高应用程序的服务质量和服务性能,也能较大地降低公司在基础设施租赁方面的费用。     

嵌入式分布实时系统自适应资源管理架构

分析了开放嵌入式分布实时(Distributed Real-time and Embedded,DRE)系统的自适应资源管理需求,针对传统静态资源管理方法的不足,提出了一种面向开放DRE系统的自适应资源管理架构;该架构采用动态任务管理、实时资源分配和自适应控制三种关键技术,能够更加适用于开放、动态的环境,有效应对资源约束和资源状态、应用程序QoS的变化;提高系统性能和稳定性;屏蔽底层硬件资源的异构性,为上层应用提供统一的服务接口。     

A two-stage approach for task and resource management in multimedia cloud environment

In recent years, multimedia cloud computing is becoming a promising technology that can effectively process multimedia services and provide quality of service (QoS) provisioning for multimedia applications from anywhere, at any time and on any device at lower costs. However, there are two major challenges exist in this emerging computing paradigm: one is task management, which maps multimedia tasks to virtual machines, and the other is resource management, which maps virtual machines (VMs) to physical servers. In this study, we aim at providing an efficient solution that jointly addresses these challenges. In particular, a queuing based approach for task management and a heuristic algorithm for resource management are proposed. By adopting allocation deadline in each VM request, both task manager and VM allocator receive better chances to optimize the cost while satisfying the constraints on the quality of multimedia service. Various simulations were conducted to validate the efficiency of the proposed task and resource management approaches. The results showed that the proposed solutions provided better performance as compared to the existing state-of-the-art approaches.     

Profile-based dynamic application assignment with a repairing genetic algorithm for greener data centers

Data centers have become essential to modern society by catering to increasing number of Internet users and technologies. This results in significant challenges in terms of escalating energy consumption. Research on green initiatives that reduce energy consumption while maintaining performance levels is exigent for data centers. However, energy efficiency and resource utilization are conflicting in general. Thus, it is imperative to develop an application assignment strategy that maintains a trade-off between energy and quality of service. To address this problem, a profile-based dynamic energy management framework is presented in this paper for dynamic application assignment to virtual machines (VMs). It estimates application finishing times and addresses real-time issues in application resource provisioning. The framework implements a dynamic assignment strategy by a repairing genetic algorithm (RGA), which employs realistic profiles of applications, virtual machines and physical servers. The RGA is integrated into a three-layer energy management system incorporating VM placement to derive actual energy savings. Experiments are conducted to demonstrate the effectiveness of the dynamic approach to application management. The dynamic approach produces up to 48% better energy savings than existing application assignment approaches under investigated scenarios. It also performs better than the static application management approach with 10% higher resource utilization efficiency and lower degree of imbalance.     

Multiversion locking protocol with freezing for secure real-time database systems

Database systems for real-time applications must satisfy timing constraints associated with transactions. Typically, a timing constraint is expressed in the form of a deadline and is represented as a priority to be used by schedulers. Recently, security has become another important issue in many real-time applications. In many systems, sensitive information is shared by multiple users with different levels of security clearance. As more advanced database systems are being used in applications that need to support timeliness while managing sensitive information, there is an urgent need to develop protocols for concurrency control in transaction management that satisfy both timing and security requirements. In this paper, we propose a new multiversion concurrency control protocol that ensures that both security and real-time requirements are met. The proposed protocol is primarily based on locking. However, in order to satisfy timing constraints and security requirements, a new method, called the freezing method, is proposed. In order to show that our protocol provides a higher degree of concurrency than existing multiversion protocols, we define a new serializability for multiversion concurrency control, called FR-serializability, which is more general than traditional serializability. We present several examples to illustrate the behavior of our protocol, along with performance comparisons with other protocols. The simulation results show significant performance improvement of the new protocol.     

Simulation of SLA-based VM-scaling algorithms for cloud-distributed applications

Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). SLAs define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.     

Sharc: managing CPU and network bandwidth in shared clusters

We argue the need for effective resource management mechanisms for sharing resources in commodity clusters. To address this issue, we present the design of Sharc-a system that enables resource sharing among applications in such clusters. Sharc depends on single node resource management mechanisms such as reservations or shares, and extends the benefits of such mechanisms to clustered environments. We present techniques for managing two important resources-CPU and network interface bandwidth-on a cluster-wide basis. Our techniques allow Sharc to 1) support reservation of CPU and network interface bandwidth for distributed applications, 2) dynamically allocate resources based on past usage, and 3) provide performance isolation to applications. Our experimental evaluation has shown that Sharc can scale to 256 node clusters running 100,000 applications. These results demonstrate that Sharc can be an effective approach for sharing resources among competing applications in moderate size clusters.     

Platform-independent modeling and prediction of application resource usage characteristics

Application resource usage models can be used in the decision making process for ensuring quality-of-service as well as for capacity planning, apart from their general use in performance modeling, optimization, and systems management. Current solutions for modeling application resource usage tend to address parts of the problem by either focusing on a specific application, or a specific platform, or on a small subset of system resources. We propose a simple and flexible approach for modeling application resource usage in a platform-independent manner that enables the prediction of application resource usage on unseen platforms. The technique proposed is application agnostic, requiring no modification to the application (binary or source) and no knowledge of application-semantics. We implement a Linux-based prototype and evaluate it using four different workloads including real-world applications and benchmarks. Our experiments reveal prediction errors that are bound within 6-24% of the observed for these workloads when using the proposed approach.     

Quality of service provisioning for distributed data center inter-connectivity enabled by network virtualization

Today’s service platform or Cloud service models, such as Infrastructure-as-a-Service (IaaS), enable customers to deploy and execute applications on an on-demand available infrastructure. Such platforms reduce operational expenses for the service provider and lower the entry barrier for small and medium enterprises. However, current commercial solutions do not provide sufficient quality of service (QoS) guarantees for some applications. For example, they do not support various interactive real-time applications.In this paper, we introduce a way overcome these current Cloud service limitations. We show how to provide and guarantee quality of service requirements for resource networks within an IaaS framework.Our work has focused on methods for network resource management and flow control as well as QoS models. We have developed a framework that enables QoS support for real-time services executing within an IaaS environment.     

构造服务质量感知的发布/订阅系统

发布/订阅系统,作为提供分布式事件检测的中间件,可支持多种应用的开发.考虑到应用提供的服务质量常常取决于发布/订阅系统的服务质量保障能力,构建了一个服务质量感知的发布/订阅系统Phoenix,并从架构、可靠性保障机制、及时性保障机制等多方面来提升系统的服务质量.因此, Phoenix能成功应对通信链路故障、代理故障和集群抖动,从而保障了应用的正常运行,同时,它能尽力而为地满足用户指定的及时性需求.实验结果表明Phoenix的可靠性好,能较好地支持用户的及时性需求.     

HeiRAT - Quality-of-service management for distributed multimedia systems

Multimedia systems must be able to support a certain quality of service (QoS) to satisfy the stringent real-time performance requirements of their applications. HeiRAT, the Heidelberg Resource Administration Technique, is a comprehensive QoS management system that was designed and implemented in connection with a distributed multimedia platform for networked PCs and workstations. HeiRAT includes techniques for QoS negotiation, QoS calculation, resource reservation, and resource scheduling for local and network resources.     

An Algebraic QoS-Based Resource Allocation Model for Competitive Multimedia Applications

A new class of multimedia applications require new mechanisms to consider various Quality of Services with respect to resource constraints so that they could support reliable services and utilize available resources optimally. In this paper we present a new analytical and generic resource management model that is QoS-based. The approach for resource allocation and relevant algorithms is based on a mathematically proved model that manages resource and QoS allocation intelligently so that the total system utility of is maximized. We use the constructs of application benefit functions and resource demand functions to represent the system configuration and to solve the resource allocation problems. Extensive surveys on the related work including systematic and analytical approaches are also presented.     

Scheduler Modeling Based on the Controller Synthesis Paradigm

The controller synthesis paradigm provides a general framework for scheduling real-time applications. Schedulers can be considered as controllers of the applications; they restrict their behavior so that given scheduling requirements are met. We study a modeling methodology based on the controller synthesis paradigm. The methodology allows to get a correctly scheduled system from timed models of its processes in an incremental manner, by application of composability results which simplify schedulability analysis. It consists in restricting successively the system to be scheduled by application of constraints defined from scheduling requirements. The latter are a conjunction of schedulability requirements that express timing properties of the processes and policy requirements about resource management. The presented methodology allows a unified view of scheduling theory and approaches based on timing analysis of models of real-time applications.     

一种新的等效带宽估计方法

网络技术和图像语音处理技术的发展促进了多媒体通信技术的发展,随着分级交换网中多媒体通信研究的深入,多媒体流的适时性问题得到了特别的关注,在实时多媒体应用中,同包丢失率一样,时延也是一个重要的性能指标,在综合考虑多媒体业务的统计特性以及包丢失率和时延等QoS参数影响的基础上,给出了一个计算简单且便于实时带宽估计和管理的多媒体业务等效带宽的近似表达式,并讨论了相关参数对等效带宽的影响。