一种基于能耗优化的云计算系统任务调度方法

服务器执行任务产生的能耗是云计算系统动态能耗的重要组成部分。为降低云计算系统任务执行的总能耗,提出了一种基于能耗优化的最早完成时间任务调度方法,建立了服务器动态功率计算模型,基于动态功率的服务器执行能耗模型,以及云计算系统的能耗优化模型。调度策略根据任务的截止时间要求和在不同服务器上的执行能耗,选择不同的调度算法,以获得最小任务执行总能耗。实验结果证明,提出的任务调度方法,能够较好地满足任务截止时间的要求,降低云计算系统任务执行的总能耗。     

随机任务在云计算平台中能耗的优化管理方法

针对云计算系统在运行过程中由于计算节点空闲而产生大量空闲能耗,以及由于不匹配任务调度而产生大量“奢侈”能耗的能耗浪费问题,提出一种通过任务调度方式的能耗优化管理方法.首先,用排队模型对云计算系统进行建模,分析云计算系统的平均响应时间和平均功率,建立云计算系统的能耗模型.然后提出基于大服务强度和小执行能耗的任务调度策略,分别针对空闲能耗和“奢侈”能耗进行优化控制.基于该调度策略,设计满足性能约束的最小期望执行能耗调度算法ME3PC(minimum expectation execution energy with performance constraints).实验结果表明,该算法在保证执行性能的前提下,可大幅度降低云计算系统的能耗开销.     

移动边缘计算中资源受限的串行任务卸载策略

云计算和移动互联网的不断融合，促进了移动云计算的产生和发展，但是其难以满足终端应用对带宽和延迟的需求.移动边缘计算在靠近用户的网络边缘提供计算和存储能力，通过计算卸载，将终端任务迁移至边缘服务器上面执行，能够有效降低应用延迟和节约终端能耗.然而，目前针对移动边缘环境任务卸载的主要工作大多考虑单个移动终端和边缘服务器资源无限的场景，这在实际应用中存在一定的局限性.因此，针对边缘服务器资源受限下的任务卸载问题，提出了一种面向多用户的串行任务动态卸载策略（multi-user serial task dynamic offloading strategy，简称MSTDOS）.该策略以应用的完成时间和移动终端的能量消耗作为评价指标，遵循先来先服务的原则，采用化学反应优化算法求解，充分考虑多用户请求对服务器资源的竞争关系，动态调整选择策略，为应用做出近似最优的卸载决策.仿真结果表明，MSTDOS策略比已有算法能够取得更好的应用性能.     

多无人机协同直播场景下自适应任务卸载决策

针对多无人机协同执行任务过程中计算量大和能耗高的问题,基于计算卸载原理以及博弈理论,提出一种多无人机自适应任务卸载方案.在方案中首先对系统进行建模,构造出多节点相互制约的移动卸载模型;其次,根据卸载模型分别构建无人机执行任务时的时延与能耗计算方法,通过综合考虑延时和能耗两方面因素,生成系统全局代价函数;然后,设计出基于博弈理论和纳什均衡的自适应任务卸载算法,通过卸载算法与权重的分配实现最优计算节点的选取,实现整个直播系统的代价最小,从而平衡无人机计算时延与能量消耗;最后,与现有卸载模型相比,所提出的方案在任务执行过程中具有较强的移动性,能耗更低且时效性更高.仿真结果验证了所提出理论的有效性,具有现实意义.     

边缘计算中基于能耗感知的容错协同任务执行算法

边缘计算已被设想成为增强资源贫乏的智能设备计算能力的有效解决方案.通过任务卸载用户可以将计算复杂的任务卸载到边缘云端执行来满足其对资源的需求.然而,其仍然需要解决能量消耗、可靠性和延时的问题.文中提出了一种基于能耗感知的容错协同任务执行算法,以在减少设备能耗的同时保证卸载到边缘云上的任务成功执行.具体地,首先设计了一种具有容错能力的能耗感知协同任务执行模型,该模型通过将计算卸载模型和容错模型相结合,从而在应用程序的截止完成时间内减少设备能耗.然后,提出了一种基于能耗感知的容错协同任务执行调度算法,该算法包括协同任务执行、初始化调度和在线调度.协同任务执行是通过部分关键路径分析和one-climb策略来确定任务的执行决策;初始化调度是从副本和重新提交中为在边缘端执行的任务选择容错策略,以在发生故障时可针对任务采取相应容错措施;在线调度是在发生故障时实时调整容错策略以确保任务成功处理.最后,在3种具有代表性的任务拓扑上进行了广泛的仿真实验,评估了3种不同方案在任务完成率、能耗比方面的性能差异.结果表明,无论是截止完成时间、传输速率还是容错率的变化,该方法都可以保证任务在截止时间内顺利完成,相比协同任务执行更可靠,而且相比本地执行设备消耗的能量可至少减少30％.     

基于动态性有效资源分配的云计算效益学习模型研究

为了将有限的资源合理地分配给用户,并尽可能地提高云系统的资源和能量利用效率,提出了一种改进的面向动态性有效资源分配的云计算效益学习模型算法,在动态性有效资源分配上提出了服务质量准则框架(QSSF)来得出云服务的计费管理机制;采用资源竞拍策略和动态双向博弈策略更好地权衡用户和云计算提供商之间的利益关系,并将资源分配给资源需求量大的用户;在云系统的运算和存储任务的资源和能量分配上,采用了基于云计算的效益学习模型,通过权衡任务对资源和能量的需求量来实现系统效益的最优化;实验仿真结果表明,该算法能够更加合理地为系统的运算和存储任务分配资源和能量,在资源和能量的利用率上优于其他对比算法.     

云工作流系统中能耗感知的任务调度算法*

云工作流系统研究集中在工作流任务执行的时间效率优化,然而时间最优的任务调度方案可能存在不同能耗,因此,文中求解满足时间约束时能耗最优的调度方案。首先改进任务执行能耗模型,设计适用于评价任务调度方案执行能耗的适应度计算方法。然后基于精准调整粒子速度的自适应权重,提出解决任务调度能耗优化问题的自适应粒子群算法。实验表明,文中算法收敛稳定,调度方案执行能耗较低。     

基于一致性树分布的数据分布式存储方法

随着云计算和大数据技术的发展,传统的单一存储介质的数据存储方式已经不能满足大数据处理的需求,在这样的背景下,分布式数据存储得到了广泛的应用。然而,目前存在的几种分布式存储方式并不能够完美地满足分布系统的需求。为了更有效地实现数据的分布式存储和冗余备份,采用一种新的基于一致性树分布(CTD)的分布式存储方法,并提出基于该方法的备份策略,实现数据索引与存储位置的映射。该方案具有负载平衡、无单点故障问题、扩展性高且易于实现的优点。同时提出了基于一致性二叉树分布(CBTD)的应用方案。通过对应用系统实例的分析,验证该方法能够很好地满足分布式系统的数据平衡、负载均衡和扩展性需求。     

云计算环境下的节能任务调度策略的随机Petri网分析

针对当前云计算异构服务器集群环境下的高能耗问题,提出一种最小能耗优先的任务调度策略(first sche-duling with minimum energy)。该策略在调度任务时优先考虑处于运行状态的服务器,并以任务响应时间为约束,按照最小能耗原则将任务分配到相应的服务器上执行。当处于运行状态的服务器都不能满足任务对响应时间的要求时,则考虑处于休眠状态的服务器;同时,也基于最小能耗原则进行调度。采用随机Petri网工具对节能任务调度策略进行分析建模,考虑其能耗和相关性能指标。实验结果表明,该方法不仅能满足任务的QoS性能要求,而且具有较好的节能效果。     

支持嵌入式操作系统的ARM能耗模拟器设计*

常见的嵌入式系统能耗模拟器不支持操作系统环境下的能耗模拟,无法获取操作系统环境下嵌入式软件的能耗模拟数据。针对这个问题,提出支持嵌入式Linux操作系统的ARM能耗模拟器设计。能耗模拟器设计采用基于任务的能耗分析策略,通过利用任务能耗表和函数调用能耗栈机制解决在操作系统环境下能耗模拟遇到的能耗混杂难题,能够准确地模拟每个并发运行程序的能量消耗。实验结果表明,该能耗模拟器能够满足嵌入式操作系统环境下的软件能耗模拟要求。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.