A framework for the deployment of adaptable web service compositions

The basic paradigm of service-oriented architectures—publication, discovery, and use—can be interpreted in different ways. Current technologies assume a static and rigid approach: UDDI was conceived with the idea of a centralized repository for service publication and BPEL only supports design–time bindings between the orchestrated workflow and the external services. The trend, however, is towards more flexibility and dynamism. The single centralized repository is being substituted by dedicated repositories that cooperate and exchange information about stored services on demand. Design–time compositions are complemented by mechanisms to allow for the selection and binding of services at runtime. This paper presents the research results of our group in delivering a framework for the deployment of adaptable Web service compositions. The publication infrastructure integrates existing heterogeneous repositories and makes them cooperate for service discovery. The deployment infrastructure supports BPEL-like compositions that can select services dynamically, and also adjust their behavior in response to detected changes and unforeseen events. The framework also provides a monitoring-based validation of running compositions: we provide suitable probes to oversee the execution of deployed compositions. The various parts of the framework are exemplified on a common case study taken from the automotive domain. This research is partially supported by the European IST project SeCSE (Service Centric System Engineering) and the Italian FIRB project ARTDECO (Adaptive infRasTructures for DECentralized Organizations).     

FlexRFID: A design,development and deployment framework for RFID-based business applications

The surge of RFID technology and ensuing competition in the RFID vendor market has increased the complexity of integration of RFID into current business processes. To address this problem, we present FlexRFID, a modeling template composed of state indicators, conditions, a simulation engine, and a device-independent deployment architecture for rapid prototyping of control applications using RFID and sensor hardware. The modeling technique is based on Moore Machines, a variant of finite state automata that allow states to be associated with outputs. With FlexRFID, users design applications by modeling business logic via transition of states based on sensor events. Outputs associated with individual states can handle operational characteristics of the application. In this article, we present the modeling methodology and demonstrate how organizations can develop complex applications easily using FlexRFID. We believe that the simplicity and flexibility of FlexRFID will lead to the development of RFID applications quickly even with limited resources. In addition, the parking entry application presented in our paper demonstrates FlexRFID’s capability of being used in business application context, as well as in research, training, and teaching.     

动态资源感知的并行化模糊测试框架

针对现有的并行模糊测试在测试效率、资源利用率以及异常处理上的局限性,本文围绕测试资源的生成、使用及容错三个方面提出了一种动态资源感知的系统化解决方案。针对测试环境在大规模和多场景两个维度快速搭建的需求,提出一种基于云平台的动态构建方法,加快测试环境部署,提高有效fuzz时间;针对并行模糊测试中资源利用率低的问题,提出一种多层次并行度动态调整的资源配置策略,优化整体测试资源配置并提高单机负载;针对大规模并行测试中节点易发生故障的问题,提出基于优先级调度的容错处理方法。最后,本文设计并实现了一个基于四级流水线并行处理结构的通用模糊测试框架。实验证明,该框架能够有效提高并行模糊测试的测试效率和资源利用率,实现系统的有效容错。     

A formal framework for service mashups with dynamic service selection

The service mashup programming paradigm is a blooming faction of service oriented Architecture for developing web applications. A mashup application constructs its functionality by combining data, presentation and functionalities obtained from online services published by service providers such as Google and Amazon. This paradigm significantly facilitates the implementation of application and reduces the workload. But it also makes the application rely on the availability and qualities of the online services which beyond its control in which case the robustness of the system requires more concern. This paper proposes a formal model to specify and analyze the behavior and robustness of service mashups under a certain environment where some services may become unavailable. The specification contains both system specification and environment situation. Refinement theory are employed to specify the correctness of dynamic service selection. The framework realizes the service selection by allowing virtual service requests to be handled by any online service having consistent interface and refined functionality. The framework provides a clear definition of the robustness of mashup systems and proposes several rules as well as approaches to preserve the robustness during the development and maintenance of the system.     

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.     

A lightweight Web service enabled framework for ubiquitous RFID applications

RFID can give a unique digital identifier to real physical object, and bridge the physical world with the virtual digital world. Based on the analysis on our experience of RFID applications, some common key issues and requirements of RFID application are presented. A lightweight framework based on Web Service to support ubiquitous RFID application is designed and implemented. This lightweight framework provides the integration of RFID technology and other holistic applications. Virtual object is used to map the real physical world object and the virtual digital object. The experiment result is given and some future research directions are discussed.     

服务网格虚拟服务动态部署和自适应策略

以"服务"的形式包装网格资源已成为一种趋势,并得到网格界的一致认可.为了更加充分灵活的利用网格资源,提出了一个网格虚拟服务动态部署架构以及基于此架构的服务平衡调度算法,通过服务按需部署和实时监控,动态调整资源在不同任务间的分配,并在需要时进行任务迁移,保证应用的服务质量.实验结果表明此系统较其它系统在资源利用率、QoS命中率上都有一定的提高.     

Lightweight migration for web applications with framework separation

Web applications (apps) are programs created by web technologies such as HTML, CSS, and JavaScript. Web apps can be executed on any platform that supports a web browser. Such portability allows an interesting user experience called app migration, which can save an app's execution state to a file called snapshot, transmit it to another device, and continue the execution using the snapshot. However, existing approaches save all the states of the current app, regardless of its relevance to an app's state, making the snapshot size and snapshot creation time infeasibly large. For example, web apps are often programmed using web frameworks such as jQuery, which are libraries written in JavaScript to support app developments. We found that most objects created by frameworks during their initialization are not relevant to an app's state. Hence, one idea to reduce the snapshot size is not saving those framework objects in the snapshot but creating them after migration via re‐initialization. Unfortunately, this is not always straightforward since the framework objects are intermingled with the app objects in the heap, possibly pointing to each other. To resolve this, we separated app objects that are attached to framework objects by monitoring app's execution and saved them to the snapshot. This paper proposes such a framework separated migration technique, with optimization to reduce the overhead, especially related to monitoring app's execution. With our approach, we could reduce the snapshot size by 89.1% on average and shorten the migration time by 47.6%, increasing the feasibility of app migration.     

A framework for software process deployment and evaluation

ContextSoftware Process Engineering promotes the systematic production of software by following a set of well-defined technical and management processes. A comprehensive management of these processes involves the accomplishment of a number of activities such as model design, verification, validation, deployment and evaluation. However, the deployment and evaluation activities need more research efforts in order to achieve greater automation.ObjectiveWith the aim of minimizing the required time to adapt the tools at the beginning of each new project and reducing the complexity of the construction of mechanisms for automated evaluation, the Software Process Deployment & Evaluation Framework (SPDEF) has been elaborated and is described in this paper.MethodThe proposed framework is based on the application of well-known techniques in Software Engineering, such as Model Driven Engineering and Information Integration through Linked Open Data. It comprises a systematic method for the deployment and evaluation, a number of models and relationships between models, and some software tools.ResultsAutomated deployment of the OpenUP methodology is tested through the application of the SPDEF framework and support tools to enable the automated quality assessment of software development or maintenance projects.ConclusionsMaking use of the method and the software components developed in the context of the proposed framework, the alignment between the definition of the processes and the supporting tools is improved, while the existing complexity is reduced when it comes to automating the quality evaluation of software processes.     

UDPF: A unified data provision framework for developing dynamic resource-oriented embedded applications

With the popularity of various embedded applications, there is increasing demand for automatic updates with low bandwidth overhead. In this paper, a developing framework based on the Android platform called the Unified Data Provision Framework (UDPF) is proposed. The UDPF provides a framework with which developers are able to build applications with modules that are decoupled from each other. In the UDPF, applications are divided into two independent layers: the front-end and back-end. Developers are able to publish updates for their applications in the minimal replacement unit with low bandwidth overhead, and it is not necessary to re-install the applications. We build a social network application using UDPF and conduct a performance evaluation that demonstrates the effectiveness of UDPF.     

Adaptive resource management for dynamic distributed real-time applications

The dynamic distributed real-time applications run on clusters with varying execution time, so re-allocation of resources is critical to meet the applications’s deadline. In this paper we present two adaptive recourse management techniques for dynamic real-time applications by employing the prediction of responses of real-time tasks that operate in time sharing environment and run-time analysis of scheduling policies. Prediction of response time for resource reallocation is accomplished by historical profiling of applications’ resource usage to estimate resource requirements on the target machine and a probabilistic approach is applied for calculating the queuing delay that a process will experience on distributed hosts. Results show that as compared to statistical and worst-case approaches, our technique uses system resource more efficiently.     

移动边缘计算中资源受限的动态服务部署策略

移动边缘计算（MEC）的出现使移动用户能够以低延迟访问部署在边缘服务器上的服务。然而,MEC仍然存在各种挑战,尤其是服务部署问题。边缘服务器的数量和资源通常是有限的,只能部署数量有限的服务;此外,用户的移动性改变了不同服务在不同地区的流行度。在这种情况下,为动态请求部署合适的服务就成为一个关键问题。针对该问题,通过了解动态用户请求来部署适当的服务以最小化交互延迟,将服务部署问题表述为一个全局优化问题,并提出了一种基于集群划分的资源聚合算法,从而在计算、带宽等资源约束下初步部署合适的服务。此外,考虑动态用户请求对服务流行度及边缘服务器负载的影响,开发了动态调整算法来更新现有服务,以确保服务质量（QoS）始终满足用户期望。通过一系列仿真实验验证了所提出策略的性能。仿真结果表明,与现有基准算法相比,所提出的策略可以降低服务交互延迟并实现更稳定的负载均衡。     

MultiOff: offloading support and service deployment for multiple IoT applications in mobile edge computing

The Journal of Supercomputing - Mobile Edge Computing (MEC) provides a new opportunity to reduce the latency of IoT applications significantly. It does so by offloading computation-intensive tasks...     

A lightweight active service migration framework for computational offloading in mobile cloud computing

Cloud computing enables access to the widespread services and resources in cloud datacenters for mitigating resource limitations in low-potential client devices. Computational cloud is an attractive platform for computational offloading due to the attributes of scalability and availability of resources. Therefore, mobile cloud computing (MCC) leverages the application processing services of computational clouds for enabling computational-intensive and ubiquitous mobile applications on smart mobile devices (SMDs). Computational offloading frameworks focus on offloading intensive mobile applications at different granularity levels which involve resource-intensive mechanism of application profiling and partitioning at runtime. As a result, the energy consumption cost (ECC) and turnaround time of the application is increased. This paper proposes an active service migration (ASM) framework for computational offloading to cloud datacenters, which employs lightweight procedure for the deployment of runtime distributed platform. The proposed framework employs coarse granularity level and simple developmental and deployment procedures for computational offloading in MCC. ASM is evaluated by benchmarking prototype application on the Android devices in the real MCC environment. It is found that the turnaround time of the application reduces up to 45 % and ECC of the application reduces up to 33 % in ASM-based computational offloading as compared to traditional offloading techniques which shows the lightweight nature of the proposed framework for computational offloading.     

面向电力无线业务的上行动态资源调度算法

电网作为一个典型的物联网应用,电力无线专网上行调度过程中存在业务服务质量得不到保障、系统吞吐量低和资源分配不连续等问题,因此提出了基于业务优先级的电力无线专网上行动态资源调度算法。通过研究电力无线专网承载业务的特点,对业务优先级进行评定,并结合TD-LTE资源分配的特点,针对不同业务设计不同的调度方法。仿真结果表明,所提算法能有效提高系统吞吐量,并保障业务Qo S,改善业务传输性能。     

软件定义广域网中控制器部署与交换机动态迁移策略

在软件定义广域网（SD-WAN）部署中，由于广域网（WAN）覆盖范围极大这一特性，单控制器部署策略无论在容量、负载还是安全方面都无法满足其需求，多控制器的部署成为必然趋势。而多控制器部署后整体网络的静态配置很难适应动态的网络流变化，从而造成控制器的负载不均衡，整体网络性能降低。针对上述问题，提出一种多控制器部署算法SC-cSNN，以有效减小控制器和交换机之间的传播时延；并提出一种基于时延、控制器容量以及控制器安全等特征的交换机动态迁移算法，以有效解决控制器超负载问题。仿真实验结果表明，SC-cSNN控制器部署算法的平均最大时延优于现有的基于k-means和基于谱聚类的控制器部署算法，交换机动态迁移算法从多特征的角度有效地解决了SD-WAN控制器负载不均衡的问题。     

IaaS环境下多租户安全资源分配算法和安全服务调度框架

针对基础设施即服务（IaaS）环境下多租户使用安全服务时由于安全资源有限和安全资源分配不均导致的效率低下问题,提出了一个租户安全资源调度框架。首先以最小最大公平算法为基础,结合Fair Scheduler的调度思想为租户设定了最小共享量和资源需求量属性;然后通过安全服务资源分配算法在保证租户最小共享量满足的前提下,尽可能公平地满足租户的资源需求;最后结合租户内任务调度和租户间资源抢占算法,实现了租户安全服务调度框架。实验结果表明,在随机资源分配条件下,安全服务资源分配算法与传统资源分配算法相比在资源利用率和作业效率上均有明显提高,安全服务调度框架可以有效解决多租户安全资源的分配和强占问题。     

面向大数据复杂应用的虚拟集群动态部署模型

针对计算负载的时变性和复杂性导致虚拟集群的资源利用率不高的问题,为提高虚拟集群资源的全局利用率,采用弹性资源管理策略来吸收多种计算模式混杂时的资源需求突变。在Docker容器技术的支持下提出一个根据作业需求变化的动态部署模型。该模型根据资源的动态需求变化,实时调整虚拟集群的计算形态,具体包括计算节点的类型及规模。该模型不仅实现用户作业执行环境的动态定制,而且达到错峰计算的目的。仿真实验表明,该模型使得虚拟节点CPU利用率提升5.3%,并且优化了计算作业的执行效率。该动态部署模型适合应用到数据中心或大规模集群中,能够有效提高计算资源的利用率。