An adaptive model-free resource and power management approach for multi-tier cloud environments

With the development of cloud environments serving as a unified infrastructure, the resource management and energy consumption issues become more important in the operations of such systems. In this paper, we investigate adaptive model-free approaches for resource allocation and energy management under time-varying workloads and heterogeneous multi-tier applications. Specifically, we make use of measurable metrics, including throughput, rejection amount, queuing state, and so on, to design resource adjustment schemes and to make control decisions adaptively. The ultimate objective is to guarantee the summarized revenue of the resource provider while saving energy and operational costs. To validate the effectiveness, performance evaluation experiments are performed in a simulated environment, with realistic workloads considered. Results show that with the combination of long-term adaptation and short-term adaptation, the fluctuation of unpredictable workloads can be captured, and thus the total revenue can be preserved while balancing the power consumption as needed. Furthermore, the proposed approach can achieve better effect and efficiency than the model-based approaches in dealing with real-world workloads.     

A benefit-aware on-demand provisioning approach for multi-tier applications in cloud computing

Dynamic resource provisioning is a challenging technique to meet the service level agreement (SLA) requirements of multi-tier applications in virtualization-based cloud computing. Prior efforts have addressed this challenge based on either a cost-oblivious approach or a cost-aware approach. However, both approaches may suffer frequent SLA violations under flash crowd conditions. Because they ignore the benefit gained that a multi-tier application continuously guarantees the SLA in the new configuration. In this paper, we propose a benefit-aware approach with feedback control theory to solve this problem. Experimental results based on live workload traces show that our approach can reduce resource provisioning cost by as much as 30% compared with a costoblivious approach, and can effectively reduce SLA violations compared with a cost-aware approach.     

Enabling scalable parallel implementations of structured adaptive mesh refinement applications

Parallel implementations of dynamic structured adaptive mesh refinement (SAMR) methods lead to significant runtime management challenges that can limit their scalability on large systems. This paper presents a runtime engine that addresses the scalability of SAMR applications with localized refinements and high SAMR efficiencies on large numbers of processors (upto 1024 processors). The SAMR runtime engine augments hierarchical partitioning with bin-packing based load-balancing to manage the space-time heterogeneity of the SAMR grid hierarchy, and includes a communication substrate that optimizes the use of MPI non-blocking communication primitives. An experimental evaluation on the IBM SP2 supercomputer using the 3-D Richtmyer-Meshkov compressible turbulence kernel demonstrates the effectiveness of the runtime engine in improving SAMR scalability.

A resource elasticity framework for QoS-aware execution of cloud applications

Cloud infrastructures consisting of heterogeneous resources are increasingly being utilized for hosting large-scale distributed applications from diverse users with discrete needs. The multifarious cloud applications impose varied demands for computational resources along with multitude of performance implications. Successful hosting of cloud applications necessitates service providers to take into account the heterogeneity existing in the behavior of users, applications and system resources while respecting the user’s agreed Quality of Service (QoS) criteria. In this work, we propose a QoS-Aware Resource Elasticity (QRE) framework that allows service providers to make an assessment of the application behavior and develop mechanisms that enable dynamic scalability of cloud resources hosting the application components. Experimental results conducted on the Amazon EC2 cloud clearly demonstrate the effectiveness of our approach while complying with the agreed QoS attributes of users.     

IC cloud: Enabling compositional cloud

Cloud computing has attracted great interest from both academic and industrial communities. Different paradigms, architectures and applications based on the concept of cloud have emerged. Although many of them have been quite successful, efforts are mainly focusing on the study and implementation of particular setups. However, a generic and more flexible solution for cloud construction is missing. In this paper, we present a composition-based approach for cloud computing (compositional cloud) using Imperial College Cloud (IC Cloud) as a demonstration example. Instead of studying a specific cloud computing system, our approach aims to enable a generic framework where various cloud computing architectures and implementation strategies can be systematically studied. With our approach, cloud computing providers/adopters are able to design and compose their own systems in a quick and flexible manner. Cloud computing systems will no longer be in fixed shapes but will be dynamic and adjustable according to the requirements of different application domains.     

利用ASP和DCOM技术构建多层分布式应用

在论述ASP和DCOM技术基础上，阐述ASP和DCOM在多层分布式上的具体应用。     

Joint‐analysis of performance and energy consumption when enabling cloud elasticity for synchronous HPC applications

A key characteristic of cloud computing is elasticity, automatically adjusting system resources to an application's workload. Both reactive and horizontal approaches represent traditional means to offer this capability, in which rule‐condition‐action statements and upper and lower thresholds occur to instantiate or consolidate compute nodes and virtual machines. Although elasticity can be beneficial for many HPC (high‐performance computing) scenarios, it also imposes significant challenges in the development of applications. In addition to issues related to how we can incorporate this new feature in such applications, there is a problem associated with the performance and resource pair and, consequently, with energy consumption. Further exploring this last difficulty, we must be capable of analyzing elasticity effectiveness as a function of employed thresholds with clear metrics to compare elastic and non‐elastic executions properly. In this context, this article explores elasticity metrics in two ways: (i) the use of a cost function that combines application time with different energy models; (ii) the extension of speedup and efficiency metrics, commonly used to evaluate parallel systems, to cover cloud elasticity. To accomplish (i) and (ii), we developed an elasticity model known as AutoElastic, which reorganizes resources automatically across synchronous parallel applications. The results, obtained with the AutoElastic prototype using the OpenNebula middleware, are encouraging. Considering a CPU‐bound application, an upper threshold close to 70% was the best option for obtaining good performance with a non‐prohibitive elasticity cost. In addition, the value of 90% for this threshold was the best option when we plan an efficiency‐driven execution. Copyright © 2015 John Wiley & Sons, Ltd.     

CDA: a novel multicore scheduling for cost-aware deadline-constrained scientific workflows on the IaaS cloud

The Journal of Supercomputing - The variety of pricing models offered by cloud service providers and the availability of a wide diversity of computing resources has increased the popularity of this...     

基于服务时间标记的多层Web应用性能异常侦测方法*

提出一种基于服务时间标记的性能异常侦测方法,标记相对稳定的请求服务时间,并通过分析该时间变化来定位性能瓶颈以及分析可能的原因。该方法已经实现在一个典型的多层Web应用系统的支撑平台中,TPC-W测试基准的测试结果验证了其有效性。     

面向云应用的拟态云服务架构

针对单执行体的云应用服务缺乏异构性和动态性,难以应对未知漏洞和后门的安全威胁问题,提出一种拟态云服务架构,把云平台向用户提供的应用服务节点构造成基于拟态防御技术的服务包,使应用服务具有拟态构造带来的内生安全特性和鲁棒性,同时讨论了策略调度和裁决机制等两项关键的拟态云服务运行机制.经实验分析表明,拟态云服务具有较好的安全...     

Enabling QoS adaptation decisions for Internet applications

We present a network model that allows processing of QoS (quality of service) information about media flows to enable applications to make adaptation decisions. Our model is based around a multi-dimensional spatial representation that allows QoS information describing the flow constructions and QoS parameters – flow-states – to interact with a representation of the network QoS. The model produces reports about the compatibility between the flow-states and the network QoS, indicating which flow-states the network can currently support. The simple nature of the reports allows the application to make decisions, dynamically, on which flow-state it should use. The model is relatively lightweight and scaleable. We demonstrate the use of the model by simulation of a dynamically adaptive audio tool. Our work is ongoing.     

Enabling device independent co-browsing through adaptive view points

Efficient co-browsing of web-pages from devices with different capabilities requires users to have a shared understanding of those web-pages. This paper outlines the concept of shared view point (SVP) and personal view point (PVP) for co-browsing before detailing a framework for implementing these concepts and some of the algorithms involved. Particular emphasis is given to the display structure and semantic grouping of web-page objects and the subsequent repositioning of the same in the different view points. The effectiveness of the system is demonstrated through a perceptual experiment.     

Enabling ubiquitous sensor-assisted applications on the internet-of-things

The increase in sensor-assisted applications such as sensing campaigns and interactions in large-scale populations put new demands on seamless sharing of sensor information on a global scale. Existing support is limited due to simplified information models reflecting narrow application scenarios and poorly scaling architectures. In response to this, we present an application architecture for pervasive internet-of-things applications which circumvents these limitations. Our architecture enables applications to utilize information from sensors and wireless sensor networks via a peer-to-peer overlay. The overlay shares sensor information in an generic information model, which is extensible and thus enables intelligent application behavior. Our evaluation of the architecture indicates that it supports the sharing of sensor information on a global scale in sensor-assisted applications, with low response times. Finally, we evaluate the feasibility of running such applications in end devices with limited resources in a sensor-assisted application prototype.     

Digital provenance: Enabling secure data forensics in cloud computing

Secure provenance that records the ownership and process history of data objects is vital to the success of data forensics in cloud computing. In this paper, we propose a new secure provenance scheme based on group signature and attribute-based signature techniques. The proposed provenance scheme provides confidentiality on sensitive documents stored in a cloud, unforgeability of the provenance record, anonymous authentication to cloud servers, fine-grained access control on documents, and provenance tracking on disputed documents. Furthermore, it is assumed that the cloud server has huge computation capacity, while users are regarded as devices with low computation capability. Aiming at this, we show how to utilize the cloud server to outsource and decrease the user’s computational overhead during the process of provenance. With provable security techniques, we formally demonstrate the security of the proposed scheme under standard assumptions.     

Enabling the generation of web applications from mockups

Mockups are widely used to elicit and validate user requirements in web applications, and several intuitive tools have been developed in recent years, actively involving the end user in the requirements solicitation process. However, most current web development approaches and tools discard mockups after the information‐gathering process, abandoning the opportunity to exploit underlying information in them for autogenerating functional web applications. To overcome this limitation, we have devised a method for deriving the database schema and the logic of the web application from the information contained within mockups. In particular, the method gathers clues on how to organize the data and the control flow of the web application by analyzing the structure and relationships of the widgets in the mockup. Based on the proposed method, we have implemented a tool supporting the generation of web applications abiding by the model‐view‐controller architectural pattern. The tool has been evaluated by involving several end users in the development of web applications for different domains.     

Research on resource allocation for multi-tier web applications in a virtualization environment

Resource allocation for multi-tier web applications in virtualization environments is one of the most important problems in autonomous computing. On one hand, the more resources that are provisioned to a multitier web application, the easier it is to meet service level objectives (SLO). On the other hand, the virtual machine which hosts the multi-tier web application needs to be consolidated as much as possible in order to maintain high resource utilization. This paper presents an adaptive resource controller which consists of a feedback utilization controller and an auto-regressive and moving average model (ARMA)-based model estimator. It can meet application-level quality of service (QoS) goals while achieving high resource utilization. To evaluate the proposed controllers, simulations are performed on a testbed simulating a virtual data center using Xen virtual machines. Experimental results indicate that the controllers can improve CPU utilization and make the best tradeoff between resource utilization and performance for multi-tier web applications.     

Virtualization-based autonomic resource management for multi-tier Web applications in shared data center

As large data centers emerge, which host multiple Web applications, it is critical to isolate different application environments for security reasons and to provision shared resources effectively and efficiently to meet different service quality targets at minimum operational cost. To address this problem, we developed a novel architecture of resource management framework for multi-tier applications based on virtualization mechanisms. Key techniques presented in this paper include (1) establishment of the analytic performance model which employs probabilistic analysis and overload management to deal with non-equilibrium states; (2) a general formulation of the resource management problem which can be solved by incorporating both deterministic and stochastic optimizing algorithms; (3) deployment of virtual servers to partition resource at a much finer level; and (4) investigation of the impact of the failure rate to examine the effect of application isolation. Simulation experiments comparing three resource allocation schemes demonstrate the advantage of our dynamic approach in providing differentiated service qualities, preserving QoS levels in failure scenarios and also improving the overall performance while reducing the resource usage cost.     

Enabling distributed Corba access to smart card applications

The OrbCard framework uses Corba wrapper technology to extend smart card services to a distributed computing environment     

Component-based tailorability: Enabling highly flexible software applications

Component technologies are perceived as an important means to keep software architectures flexible. Flexibility offered by component technologies typically addresses software developers at design time. However, the design of software which should support social systems, such as work groups or communities, also demands ‘use-time’, or technically spoken, ‘run-time’ flexibility. In this paper, we summarize a decade of research efforts on component-based approaches to flexibilize groupware applications at run-time. We address the user as a ‘casual programmer’ who develops and individualizes software for his work context. To deal with the challenges of run-time flexibility, we developed a design approach which covers three levels: software architecture, user interface, and collaboration support. With regard to the software architecture, a component model, called FlexiBeans, has been developed. The FreEvolve platform serves as an environment in which component-based applications can be tailored at run-time. Additionally, we have developed three different types of graphical user interfaces, enabling users to tailor their applications by recomposing components. To enable collaborative tailoring activities, we have integrated functions that allow sharing component structures among users. We also present different types of support techniques which are integrated into the user interface in order to enable users’ individual and collaborative tailoring activities. We conclude by elaborating on the notion of ‘software infrastructure’ which offers a holistic approach to support design activities of professional and non-professional programmers.