工业机器人能耗优化方法研究综述

机器人技术作为智能制造的关键,其能耗问题已引起各制造业大国的关注,国内外的研究十分活跃。针对工业机器人能耗优化问题,介绍了轻量化设计、高效驱动系统设计、能量存储和共享装置等低能耗硬件设计方法,从轨迹规划和任务调度方面对能耗优化的软件方法进行了综述,介绍了具有应用潜力的软件优化和硬件相结合的混合方法,同时突出了主要研究成果并说明了不足之处;最后指出工业机器人能耗优化具有潜力的发展趋势。     

基于AADL语言的移动软件能耗评估方法

移动软件往往部署在电量受限的处理器上,能耗已成为评价这类软件的一个重要质量属性.与代码级和指令级相比,在设计级进行能耗评估具有耗时短、成本低的优点,近年来已成为软件工程学术界和工业界的研究热点.目前虽已涌现出一些设计级能耗评估方法,但这些方法大多未对软件构件的内部行为元素进行能耗评估,导致了精度问题.针对上述问题,基于体系结构分析设计语言AADL和StrongARM处理器构建了一种移动软件能耗评估模型,进一步定义了面向AADL语言的移动软件能耗评估过程,在此基础上研发了一款能耗评估工具,进而提出一种基于AADL语言的移动软件能耗评估方法.实验结果表明该方法较已有AADL能耗评估方法在精度上有所提高.     

基于两级遗传算法的特定应用片上网络拓扑优化

大规模片上系统面临着性能、同步、能耗等方面的通信问题,片上网络为复杂的片上系统通信问题提供了一种有效的解决方案。由于网络拓扑优化是一种NP难问题,针对片上系统主要面向特定应用的特点,提出一种基于两级遗传算法来求解特定应用片上网络的拓扑优化问题近似解。实验结果表明,相对于现有的三级遗传,两级遗传算法在最小能耗上平均有1.1%的改进,而且仿真运行时间大大减少,平均减少97%.     

操作系统电源管理研究进展

系统级动态电源管理技术的关键问题是在系统性能与能耗之间进行权衡.在硬件提供支持的基础上,操作系统电源管理的优势在于操作系统作为系统资源管理者,根据工作负载和硬件资源电源状态的特征,在满足系统性能约束条件下作出电源管理决策和控制,降低系统能耗.从优化控制策略和操作系统资源管理的角度,综述操作系统电源管理研究现状及其关键技术.对两类动态电源管理策略进行详细分析,讨论了从资源管理角度进行操作系统电源管理的研究思路和问题,对当前面临的主要问题和发展趋势进行了总结和展望.     

一种嵌入式实时系统软件能耗建模与分析的方法

随着嵌入式实时系统低能耗研究的不断深入,软件能耗已经成为影响系统的主要因素,并朝着定量分析方向发展.针对嵌入式实时系统缺乏有效的软件能耗建模与分析的方法,提出一种基于进程代数的嵌入式实时系统软件能耗建模与分析的方法.通过在时间通信顺序进程上扩展价格信息得到价格时间通信顺序进程,将嵌入式实时系统指令的功耗映射成价格时间通信顺序进程的价格,利用价格时间通信顺序进程对嵌入式实时系统软件能耗建模并进行量化分析,提出的最优路径算法可以对建模结果进行指令功耗可满足性检查,并计算当前最低能耗可达路径.该方法可以从很大程度上提高嵌入式实时系统软件能耗计算和分析的准确性,计算结果有助于嵌入式实时系统软件能耗的量化分析和优化设计.     

嵌入式软件算法级能耗建模与分析

针对嵌入式软件算法级能耗的优化问题,建立算法级能耗估算模型。以旅行商问题(TSP)为例,采用神经网络算法、遗传算法等进行能耗求解,对求解过程中的算法执行次数、算法复杂度以及运行时间这3个特征值进行能耗分析,通过能耗估算模型计算出算法针对TSP问题的能耗估算值,并将该估算值与使用sim-panalyzer功耗仿真平台求解得到的能耗测试值进行比较,结果表明,能耗测试值与估算值的误差在10%左右,证明该能耗估算模型具有较高的准确性。     

能效查询处理与优化可行性初探

随着数据管理需求的不断增长,降低与控制数据中心的能耗成为一个挑战性问题. DBMS 是数据中心核心软件,能效查询处理与优化是其中一个重要议题. 本文提出了新型的能耗代价评估模型,通过评估查询计划的时间和能耗代价,考察了不同优化目标在不同硬件条件下对查询处理的影响. 实验表明,传统硬件下面向性能的优化与面向能耗的优化结果是一致的;在新硬件条件下,两者结果则不同,可以改进数据库系统能效.     

基于嵌入式软件算法级能耗问题研究

能耗已经成为嵌入式系统设计中一个重要的约束条件.嵌入式系统是典型的软件驱动执行系统,硬件的电路活动直接导致系统参数功耗,而软件中的指令执行和数据存取等操作底层的微处理、总线、Cache、存储器和I/O接口等硬件的活动都会间接的导致系统参数功耗.在现代“低碳经济”的背景下嵌入系统的功耗已经引起人们关注的一个重点.而软件设计早期对高层所作的功率耗评估和优化对整个系统的的能耗影响最为显著.本文通过构建算法级能耗估算模型,并通过实例采用神经网络算法、遗传算法等进行能耗求解,同时在求解过程中进行能耗分析.     

面向云计算环境的能耗测量和管理方法

云计算引领了计算机科学的一场重大变革,但与此同时,也不可避免地带来了日益凸显的能源消耗问题,因此,云计算能耗管理成为近几年的研究热点.云计算系统的能耗测量和管理直接关系到云计算的可持续发展,能耗数据不仅关系到能耗模型的建立,而且也是检验云计算资源调度算法的基础.为此,在广泛研究现有能耗测量方法的基础上,归纳总结了当前云计算环境的4种能耗测量方法:基于软件或硬件的直接测量方法、基于能耗模型的估算方法、基于虚拟化技术的能耗测量方法、基于仿真的能耗评估方法,并分析和比较了它们的优势、缺陷和适用环境.在此基础上,指出了云计算能耗管理的未来重要研究趋势:智能主机电源模块、面向不同类型应用的能耗模型、混合任务负载的能耗模型、可动态管理的高效云仿真工具、动态异构分布式集群的能耗管理、面向大数据分析处理和任务调度的节能方法以及新能源供电环境下的节能规划,为云计算节能领域的研究指明了方向.     

闪存存储系统综述

闪存因其低延迟、高并发、低能耗、体积小等特点受到了广泛关注.首先讨论了简单利用闪存固态盘替换传统磁盘的方式隐藏了闪存特性,限制了软件系统对闪存特性充分利用的不足.然后,分析并比较了现有包括闪存加速卡、闪存阵列、基于闪存的分布式集群系统等基于存储介质直接构建的闪存存储系统的特点,归纳了其通过改变硬件接口、调整软件或控制器管理模块、匹配处理器与I/O处理能力等方式实现系统低延迟、高可靠、低能耗等特性的优化方法.然后重点讨论了闪存存储系统3个方面的关键技术:基于I/O栈调整与重构的存储性能优化、系统级可靠性、体积与能耗.最后总结了闪存存储系统的现状与特点,并指出未来可能的研究方向.     

基于马尔科夫链的构件化嵌入式软件能耗估算模型

在目前全球倡导"低碳经济"的背景下,嵌入式软件能耗已成为嵌入式系统设计的重要考量因素,一种快速有效的软件能耗估算模型对于嵌入式软件早期开发具有重要的意义.本文着眼于构件化嵌入式软件,从基于状态的角度出发,将嵌入式软件系统的运行过程视为一个状态的集合,提出了一种基于马尔科夫链的嵌入式软件能耗估算模型.然后,通过使用状态转移概率矩阵获得嵌入式软件构件的稳定状态分布,再结合构件的能耗测量值,实现嵌入式软件的能耗估算,并通过实验验证了该模型的有效性.     

SEProf: A high-level software energy profiling tool for an embedded processor enabling power management functions

Energy efficiency has become one of the most important design issues for embedded systems. To examine the power consumption of an embedded system, an energy profiling tool is highly demanded. Although a number of energy profiling tools have been proposed, they are not directly applicable to the embedded processors with power management functions that are widely utilized in battery-operated embedded systems to reduce power consumption. Hence, this study presents a high-level energy profiling tool, called SEProf, that estimates the energy consumption of an embedded system running multithread software and a multitasking operating system (OS) that supports power management functions. This study implements the proposed SEProf in Linux 2.6.19 and evaluates its performance on an ARM11 MPCore processor. Experimental results demonstrate that the proposed tool can provide accurate energy profiling results with a low profiling overhead.     

Energy Metric for Software Systems

Acknowledging the intense requirement for low power operation in most portable computing systems, this paper introduces the notion of energy efficient software design and proposes metrics, for evaluating software systems in terms of their energy consumption. Considering the sources of power consumption in every digital circuit, and the fact that power is primarily dependent on the executing software, appropriate energy measures are derived, which can be extracted from the flowgraph of a program. The proposed measures are computed by applying rules common to the existing hierarchical measures of other internal software attributes, and form the basis for the definition of a software energy metric. This metric can be used in order to determine the level of energy consumption of any software system more efficiently than existing assembly-parsing techniques, with only a limited penalty in accuracy. Application to different implementations of algorithms, drawn from matrix algebra and multimedia, demonstrates the efficiency of the proposed energy metric for comparison purposes, and as an indicator for quality improvement.     

嵌入式系统源程序级软件能耗建模与分析

针对嵌入式系统能耗对各种嵌入式设备工作时长的影响,本文从系统指令级到源程序级的软件能耗考虑,首先通过分析设备源程序级语句的相关特征,基于源程序语句的指令能耗,提出一种针对源程序级的能耗模型,然后基于模型分析对五个经典算法的源程序中不同类别语句进行能耗优化,最后分别对五组经典算法优化前后的能耗比较。实验表明,本模型使得优化后的源程序能耗降低了9.46%-50.29%,达到了降低嵌入式系统软件能耗的目的。     

能耗并行加速比:高性能计算系统综合性能的有效度量

随着并行系统规模的扩大,高性能计算系统运行时消耗的能耗也在急剧增长,过高的能耗也给系统的可靠性、稳定性等方面带来严峻挑战。在这种情形下,能耗问题受到了前所未有的关注。因此,设计和研究高性能计算系统,需要在考虑高计算性能的同时兼顾系统低能耗的要求,这为高性能计算系统的度量模型提出了新的挑战。于是,大规模并行系统逐渐从"高性能"走向"高效能"的衡量标准。基于此,本文采用加速比度量指标,从系统可扩展角度将计算性能和能量消耗要素进行综合,提出了一种度量高性能计算系统综合性能的能耗并行加速比模型。该模型能够直观地反映并行计算系统的效能,旨在指导系统设计和应用研究。最后,通过对该模型的分析和模拟,验证了模型的有效性。     

Energy-monitoring tool for low-power embedded programs

Designing highly efficient embedded programs requires efficient tools to support performance monitoring and tuning of embedded software. Several such tools are available for various embedded processors. To effectively meet the energy consumption requirements of embedded systems, programmers try to understand the energy and power consumption of embedded systems as a high-priority monitoring target. The paper discusses SES, a highly integrated tool that delivers cycle-by-cycle power consumption data for optimizing embedded programs     

A parallel evolutionary algorithm to optimize dynamic memory managers in embedded systems

For the last 30 years, several dynamic memory managers (DMMs) have been proposed. Such DMMs include first fit, best fit, segregated fit and buddy systems. Since the performance, memory usage and energy consumption of each DMM differs, software engineers often face difficult choices in selecting the most suitable approach for their applications. This issue has special impact in the field of portable consumer embedded systems, that must execute a limited amount of multimedia applications (e.g., 3D games, video players, signal processing software, etc.), demanding high performance and extensive memory usage at a low energy consumption. Recently, we have developed a novel methodology based on genetic programming to automatically design custom DMMs, optimizing performance, memory usage and energy consumption. However, although this process is automatic and faster than state-of-the-art optimizations, it demands intensive computation, resulting in a time-consuming process. Thus, parallel processing can be very useful to enable to explore more solutions spending the same time, as well as to implement new algorithms. In this paper we present a novel parallel evolutionary algorithm for DMMs optimization in embedded systems, based on the Discrete Event Specification (DEVS) formalism over a Service Oriented Architecture (SOA) framework. Parallelism significantly improves the performance of the sequential exploration algorithm. On the one hand, when the number of generations are the same in both approaches, our parallel optimization framework is able to reach a speed-up of 86.40× when compared with other state-of-the-art approaches. On the other, it improves the global quality (i.e., level of performance, low memory usage and low energy consumption) of the final DMM obtained in a 36.36% with respect to two well-known general-purpose DMMs and two state-of-the-art optimization methodologies.     

嵌入式电子节能控制器的设计与实现

节能控制能够有效降低能耗,对保护环境等方面具有重要影响;但目前大多数电子节能控制器都是通过采用单片机技术和双向晶闸管过零触发交流调压电路对电子节能控制器进行设计;通过介绍电子的负荷特点和节能原理,分析电子节能控制器的硬件组成电路,并对电子节能控制器的主要软件程序的流程图进行设计,完成电子节能控制器设计;但这种方法节能控制效果较低,难以保证电子节能控制器性能,为此,提出一种基于模糊PID控制的嵌入式电子节能控制器设计与实现方法;首先通过对嵌入式电子节能控制器的处理器、电源电路、复位电路、系统时钟电路、JTAG接口电路、D/A转换电路、功放电路、双极性电源电路以及嵌入式电子节能控制器硬件PCB板器件布局等的设计,完成嵌入式电子节能控制器硬件设计;在此基础上,选用模糊PID控制方法对嵌入式电子节能控制器进行设计;通过分析模糊PID控制原理,介绍加入自调节因子的模糊PID控制的算法设计,以此确定输入输出隶属度函数,再利用模糊推理和模糊规则,得到电子节能控制器的模糊控制过程,从而完成嵌入式电子节能控制器的设计;实验证明,所提方法能够有效提高嵌入式电子节能控制器的节能控制效果,具有良好的使用价值。     

Effectiveness Analysis of DVFS and DPM in Mobile Devices

The demand for high-performance embedded processors in multimedia mobile electronics is growing and their power consumption thus increasingly threatens battery lifetime.It is usually believed that the dynamic voltage and frequency scaling (DVFS) feature saves significant energy by changing the performance levels of processors to match the performance demands of applications on the fly.However,because the energy efficiency of embedded processors is rapidly improving,the effectiveness of DVFS is expected to change.In this paper,we analyze the benefit of DVFS in state-of-the-art mobile embedded platforms in comparison to those in servers or PCs.To obtain a clearer view of the relationship between power and performance,we develop a measurement methodology that can synchronize time series for power consumption with those for processor utilization.The results show that DVFS hardly improves the energy efficiency of mobile multimedia electronics,and can even significantly worsen energy efficiency and performance in some cases.According to this observation,we suggest that power management for mobile electronics should concentrate on adaptive and intelligent power management for peripheral devices.As a preliminary design,we implement an adaptive network interface card (NIC) speed control that reduces power consumption by 10% when NIC is not heavily used.Our results provide valuable insights into the design of power management schemes for future mobile embedded systems.