An efficient job management of computing service using integrated idle VM resources for high-performance computing based on OpenStack

In recent years, various studies on OpenStack-based high-performance computing have been conducted. OpenStack combines off-the-shelf physical computing devices and creates a resource pool of logical computing. The configuration of the logical computing resource pool provides computing infrastructure according to the user’s request and can be applied to the infrastructure as a service (laaS), which is a cloud computing service model. The OpenStack-based cloud computing can provide various computing services for users using a virtual machine (VM). However, intensive computing service requests from a large number of users during large-scale computing jobs may delay the job execution. Moreover, idle VM resources may occur and computing resources are wasted if users do not employ the cloud computing resources. To resolve the computing job delay and waste of computing resources, a variety of studies are required including computing task allocation, job scheduling, utilization of idle VM resource, and improvements in overall job’s execution speed according to the increase in computing service requests. Thus, this paper proposes an efficient job management of computing service (EJM-CS) by which idle VM resources are utilized in OpenStack and user’s computing services are processed in a distributed manner. EJM-CS logically integrates idle VM resources, which have different performances, for computing services. EJM-CS improves resource wastes by utilizing idle VM resources. EJM-CS takes multiple computing services rather than single computing service into consideration. EJM-CS determines the job execution order considering workloads and waiting time according to job priority of computing service requester and computing service type, thereby providing improved performance of overall job execution when computing service requests increase.

     

面向普适计算的服务构件动态部署问题及算法

有限的资源是嵌入式应用的一个局限性,因此越来越多的嵌入式设备联网,通过共享资源为用户提供灵活的服务以适应普适计算的要求.以构件化嵌入式操作系统Liquid为背景,研究普适计算环境下多个服务构件动态部署问题,合理分配利用资源,克服单个嵌入式设备的资源局限性.首先对部署问题进行描述,然后给出服务构件动态部署的基本算法和启发式算法,并对启发式算法优化,最后通过算法模拟及数据分析算法的性能.虽然在Liquid系统上进行模拟实现,但算法具有通用性,启发式算法的效率分析表明,它适合设备或者服务构件数目较多的普适计算环境,在部署服务构件的同时提高服务准入成功率和资源的利用率.     

面向普适计算环境的Android平台服务编排框架

普适计算环境下的智能移动设备是面向终端用户的服务资源聚集和编排的主要载体。普适计算环境中的服务资源具有多种不同的形态,包括基于互联网提供的Web服务、终端设备自身服务和资源(例如本地应用、自带传感器)以及所处环境中可访问的服务(例如环境传感器)。此外,不断变化的上下文环境对软件本身的自适应能力提出了新的要求,而移动设备上的服务编排受设备计算能力和资源的限制。为了解决上述问题,提出了一个面向普适计算环境的Android平台服务编排框架ASOF。通过ASOF,移动终端可在运行时获取所需业务流程的服务模板,并对该模板中的抽象服务进行服务绑定,实现轻量级的混合服务编排,使终端能够动态获得调用普适计算环境中各种类型的服务的能力。随后,基于OSGi Felix框架给出了一套ASOF的标准实现,并以一个具体案例验证其有效性。     

A survey of service composition in ambient intelligence environments

This article presents a comparative review of systems performing service composition in Ambient Intelligence Environments. Such environments should comply to ubiquitous or pervasive computing guidelines by sensing the user needs or wishes and offering intuitive human-computer interaction and a comfortable non-intrusive experience. To achieve this goal service orientation is widely used and tightly linked with AmI systems. Some of these employ the Web Service technology, which involves well-defined web technologies and standards that facilitate interoperable machine to machine interaction. Other systems regard services of different technologies (e.g. UPnP, OSGi etc) or generally as abstractions of various actions. Service operations are sometimes implemented as software based functions or actions over hardware equipment (e.g. UPnP players). However, a single service satisfies an atomic only user need, so services need to be composed (i.e. combined), in order to provide the usually requested complex tasks. Since manual service composition is obviously a hassle for the user, ambient systems struggle to automate this process by applying various methods. The approaches that have been adopted during the last years vary widely in many aspects, like domain of application, modeling of services, composition method, knowledge representation and interfaces. This work presents a comparative view of these approaches revealing similarities and differences, while providing additional information.     

Resource collaboration system based on dynamic user preference and context

In a ubiquitous computing environment, service composition and collaboration among heterogeneous resources are required, thus, an infrastructure that supports these requirements is an essential factor in seamless service delivery. In this environment, users hope to get a variety of customized services by using only an individual mobile device. But the resource of the mobile device has limitations such as tiny display screens, limited input, less powerful processors, and limited storage. Moreover each user situation is different and user preferences are also various. Therefore it is one of new issues to provide a customized service for a user through resource collaboration based on various user preference and situation. To solve this issue, this paper proposes a resource collaboration system which infers customized resources for composing a user required service and collaborative with selected resources. For our collaboration system, this paper proposes the method to infer resources based on the context and user preferences including dynamic change of the preference. This paper also shows a reasonable execution environment for the proposed system through the performance evaluation in server-client and peer-to-peer environments.     

Cost-benefit analysis of an SLA mapping approach for defining standardized Cloud computing goods

Due to the large variety in computing resources and, consequently, the large number of different types of service level agreements (SLAs), computing resource markets face the problem of a low market liquidity. Restricting the number of different resource types to a small set of standardized computing resources seems to be the appropriate solution to counteract this problem. Standardized computing resources are defined through an SLA template. An SLA template defines the structure of an SLA, the service attributes, the names of the service attributes, and the service attribute values. However, since existing research results have only introduced static SLA templates so far, the SLA templates cannot reflect changes in user needs and market structures. To address this shortcoming, we present a novel approach of adaptive SLA matching. This approach adapts SLA templates based on SLA mappings of users. It allows Cloud users to define mappings between a public SLA template, which is available in the Cloud market, and their private SLA templates, which are used for various in-house business processes of the Cloud user. Besides showing how public SLA templates are adapted to the demand of Cloud users, we also analyze the costs and benefits of this approach. Costs are incurred every time a user has to define a new SLA mapping to a public SLA template due to its adaptation. In particular, we investigate how the costs differ with respect to the public SLA template adaptation method. The simulation results show that the use of heuristics within adaptation methods allows balancing the costs and benefits of the SLA mapping approach.     

云计算环境下实训教学平台动态迁移策略

云服务环境下最大特点是按需交付,通过虚拟化技术将相关资源构建统一调度池,并且按照用户需求为用户提供服务,因此,云服务具有并行计算、开放性以及按需交付特性.对于实训教学平台来说,在云计算环境下需要面对各种用户需求,如请求任务各种各样,实验任务类型不尽相同,设备资源存在较大差异,通过虚拟化技术来实现规范化管理何资源共享,对云资源进行调度来才能有效满足用户需求,为此,在本文中提出了云计算环境下实训教学平台动态迁移策略.策略设计了三层协同资源调度机制来实现对资源和任务管理,重点研究了任务分割、资源划分、资源调度策略等,在此基础上对系统进行仿真实验,验证云计算环境下实训教学平台动态迁移策略可行与有效性.     

普适计算环境下服务发现问题的研究与进展

普适计算环境下,环境的结构、组成以及环境中的资源、服务都是动态变化的,而服务发现技术能够在动态变化的普适计算环境中动态查找、定位所需的服务,是解决普适计算环境异构性、实现不同应用集成的有效途径,因此逐渐成为普适计算中研究的一个热点和重点。基于此,本文总结、分析了当前已有的比较著名的普适计算服务发现协议并进行了分类比较,总结了各个方向上目前的研究进展,在此基础之上对今后的研究趋势进行了分析与展望。     

Dynamic task assignment and resource management in cloud services by using bargaining solution

Cloud computing provides infrastructure, platform and software as services to customers. For the purpose of providing reliable and truthful service, a fair and elastic resource allocation strategy is essential from the standpoint of service customers. In this paper, we propose a game theoretic mechanism for dynamic cloud service management, including task assignment and resource allocation to provide reliable and truthful cloud services. A user utility function is first devised considering the dynamic characteristics of cloud computing. The elementary stepwise system is then applied to efficiently assign tasks to cloud servers. A resource allocation mechanism based on bargaining game solution is also adopted for fair resource allocation in terms of quality of service of requested tasks. Through numerical experiments, it is shown that the proposed mechanism guarantees better system performance than several existing methods. The experimental results show that the mechanism completes the requested tasks earlier with relatively higher utility while providing a significant level of fairness compared with existing ones. The proposed mechanism is expected to support cloud service providers in elastically managing their limited resources in a cloud computing environment in terms of quality of service. Copyright © 2013 John Wiley & Sons, Ltd.     

移动计算环境下的个人化服务发布和组装

随着移动计算技术的发展,移动设备用户可以服务的方式共享移动设备及其周围设备的计算能力和计算资源.然而,移动设备的私有性、资源受限性以及移动性等特征使得这种基于移动设备提供的个人化服务在发布和组装方面存在着一些特殊问题,例如用户隐私、移动设备资源消耗、网络环境变化引起的失效问题等.针对以上这些问题,提出一种移动计算环境下的个人化服务发布和组装方法.该方法在个人化服务发布过程中引入了服务意愿的概念,并在服务选择过程中综合考虑了服务意愿和服务效用.此外,还提出了资源感知的心跳机制来定期更新服务选择所依赖的设备及服务状态信息,从而解决由于网络环境变化等引起的服务失效问题.基于该方法,提出了一个基于JADE和OSGi的实现框架.通过一个案例分析,验证了所提出的实现框架的有效性以及在移动计算环境下考虑服务意愿的合理性.     

普适计算环境下的虚拟机技术研究

普适计算环境中资源和服务利用率较低,传统应用程序在该环境下无法兼容。为此,提出一种适用于普适计算环境的虚拟机技术。使用设备请求代理屏蔽复杂的普适计算网络环境,对上层应用提供统一硬件平台,支持多个普适计算应用同时运行。实验结果表明,该虚拟化技术能兼容传统应用,提高普适计算资源和服务的利用率。     

An effective offloading middleware for pervasive services on mobile devices

The practical success of pervasive services running in mobile wireless networks and devices relies on their ability to provide effective and efficient offloading support, so as to satisfy the increasing demand for mobile devices to run heavier applications (e.g. those running on desktop PCs). Offloading is an effective mechanism for leveraging the severity of resource constrained mobile devices by migrating some computing load to nearby resource-rich surrogates (e.g. desktop PCs, servers) on home networks or their extension. This paper proposes a light-weight and efficient offloading middleware, which provides runtime offloading services for resource constrained mobile devices. The middleware considers multiple types of resources (i.e. memory, CPU and bandwidth) and carries out application partitioning and partition offloading in an adaptive and efficient manner. The corresponding algorithms are presented. The evaluation outcomes indicate the effectiveness and efficiency of this service offloading solution.     

一种普及计算环境中的基础设施：PvCGrid

随着计算机技术的发展，人们希望能方便地享用计算能力和信息服务，但是由于计算设备的多样性和设备之间多传输协议的多样性，资源的描述、发现和使用方式的差异，资源之间协作缺乏统一的标准，造成了使用计算设备的障碍。该文提出了一种在普及计算环境中的基础设施——PvCGrid，实现了多种传输协议的管理、设备和服务的发现，提供了用户可定制的组合服务的功能，使得用户可以发现和使用网络中的资源，并且可以根据发现的资源，定制出更加复杂的应用，该基础设施为普及计算提供了互连互通、资源共享和协同服务的技术支持。     

普适计算认证过程基于粗糙集的隐私保护策略

在普适计算环境中,用户要获得需要的服务,需要向对应的服务提供商提供一定的认证信息,而这些认证信息中往往包含有用户不希望泄漏的隐私信息。为了对这些隐私信息进行保护,本文提出了认证过程中基于粗糙集的隐私保护策略：用户将认证信息扩展成粗糙集提供给服务提供商;服务提供商根据策略从粗糙集中提取用户的真实认证信息对用户请求进行认证。该策略充分利用了粗糙集合的不确定性,能够有效地防止用户隐私泄漏。     

A robotic service framework supporting automated integration of ubiquitous sensors and devices

In recent years, due to the emergence of ubiquitous computing technology, a new class of networked robots called ubiquitous robots has been introduced. The Ubiquitous Robotic Companion (URC) is our conceptual vision of ubiquitous service robots that provides its user with the services the user needs, anytime and anywhere, in the ubiquitous computing environments. There are requirements to be met for the vision of URC. One of the essential requirements is that the robotic systems must support ubiquity of services. This means that a robot service must always be available even though there are changes in the service environment. More specifically, a robotic system needs to be interoperable with sensors and devices in its current service environments automatically, rather than statically pre-programmed for its environment. In this paper, the design and implementation of an infrastructure for URC called Ubiquitous Robotic Service Framework (URSF) is presented. URSF enables automated integration of networked robots in a ubiquitous computing environment by the use of Semantic Web Services Technologies.     

A specification model for context-based collaborative applications

This paper presents a model for building context-based systems in pervasive computing environments from high level specifications. A pervasive computing environment is viewed as a collaboration space consisting of mobile users, system services, and sensors and resources embedded in the physical environment. The approach presented here is developed for building collaborative activities in which users and environment services cooperate towards some shared objectives and tasks. The specification model allows expression of policies related to context-based discovery and secure access of resources, and role-based interactions among users and environmental services. Using several examples we illustrate the capabilities of our specification model for expressing various kinds of context-based requirements for resource access and user interactions.     

边缘计算环境中基于规划图的服务组合修复方法

在云计算和边缘计算环境中,通过提取和组合可用的服务以满足用户需求已成为常见的做法.然而,当前的方法难以应对由于用户需求变化或外部环境变动导致的组合失效问题.为了应对这一挑战,提出一种边缘计算环境中基于规划图的服务组合及其修复方法.首先,结合移动路径模型和规划图方法完成服务组合过程,通过规划图的构建可以有效地评估和选择适合用户需求的服务组合.当服务集合发生变化或用户目标更改时,能够在现有的规划图基础上生成新的解决方案,以满足用户的需求.这种修复方法能够实时适应云边环境中的变化,提高系统的灵活性和可靠性.经过实验测试发现,所提出的修复方法相较于重新规划具有更好的性能表现,并验证了修复方法在组合失效问题上的有效性和实用性.     

一种普适环境下面向服务的事务处理模型

普适环境具有高移动、极端异构、高自治和开放性的特点,普适环境下的服务组合因其突出的动态性问题,为保证对整个服务运行结果的可靠性和一致性,引入事务处理的机制来进行管理。提出一种在普适环境下面向服务的事务处理模型,在服务的发现、组合及运行中引入事务机制来协调管理,保证了服务组合的可靠一致性,并讨论了模型的系统架构和各模块组成,及应用场景。     

COCOA: COnversation-based service COmposition in pervAsive computing environments with QoS support

Pervasive computing environments are populated with networked services, i.e., autonomous software entities, providing a number of functionalities. One of the most challenging objectives to be achieved within these environments is to assist users in realizing tasks that integrate on the fly functionalities of the networked services opportunely according to the current pervasive environment. Towards this purpose, we present COCOA, a solution for COnversation-based service COmposition in pervAsive computing environments with QoS support. COCOA provides COCOA-L, an OWL-S based language for the semantic, QoS-aware specification of services and tasks, which further allows the specification of services and tasks conversations. Moreover, COCOA provides two mechanisms: COCOA-SD for the QoS-aware semantic service discovery and COCOA-CI for the QoS-aware integration of service conversations towards the realization of the user task’s conversation. The distinctive feature of COCOA is the ability of integrating on the fly the conversations of networked services to realize the conversation of the user task, by further meeting the QoS requirements of user tasks. Thereby, COCOA allows the dynamic realization of user tasks according to the specifics of the pervasive computing environment in terms of available services and by enforcing valid service consumption.