信息物理融合系统的动态多优先级调度

信息物理融合系统(Cyber-physical Systems,CPS)的复杂和异构性给设计者带来了不少挑战,其中任务的多样性使得传统的调度策略不能满足CPS的性能需求.提出了专门针对基于大规模传感器网络的CPS的动态多优先级调度策略.根据任务类型分配4级缓存队列:第1级是来自控制器待处理的实时任务,拥有最高的可抢占式优先级;第2级是来自控制器待转发的实时任务,拥有次高的可抢占式优先级;第3级是来自其他节点待转发的非实时任务,拥有第三高的非抢占式优先级;第4级是来自本地待发送的非实时任务,拥有最低的非抢占式优先级.设计了抢占与非抢占混合的动态调度策略来减少任务的平均等待时间,加入了等待时间阈值机制来保证第4级任务的公平性.通过理论分析和仿真实验对调度策略的性能做了评价.仿真结果显示,动态多优先级调度策略在提高系统性能和稳定性上要优于传统优先级调度.     

基于虚拟现实的多感官视觉交互界面生成方法

以提升交互界面生成结果与实际物体的拟合度,为用户提供更真实的交互效果为目的,研究基于虚拟现实的多感官视觉交互界面生成方法。交互界面生成过程分为两个环节,设计内容环节包括视觉信息设计与交互方式设计,视觉信息设计中将交互界面最终布局的视觉注意力划分最优作为目标函数,设计基于视觉注意力的功能界面布局优化模型,利用粒子群算法求解该模型完成功能界面布局设计;针对功能界面中的不同区域,通过3D几何模型构建、纹理映射等过程构建三维物体与情景空间的三维模型,生成不同区域内所需图像信息。多感官视觉体验设计过程中,采用ANNS-DS信息融合算法融合传感信息、体感信息与视觉信息,基于融合结果实现虚拟现实图形显示、振动与声音反馈等界面交互功能,并结合设计内容环节中的交互方式设计提升用户对交互界面的多感官视觉体验感受。应用结果显示该方法所生成的交互界面内物体与情景空间图像的拟合度均高于0.9,可通过视觉、听觉等不同感官提升用户的体验感受。     

云计算中一种多DAG工作流可抢占式调度策略

为解决多用户工作流调度过程中的公平性问题,提高资源利用率,满足不同用户DAG工作流的不同QoS需求,提出了抢占式多DAG工作流动态调度模型。该算法将DAG工作流按照QoS需求进行优先级划分,采用高优先级作业优先占有资源的原则调度作业。相同优先级DAG工作流的任务依据带有启发性信息的slowdown进行资源抢占,进一步提高了作业调度的公平性;对于不同优先级的作业调度,提出了基于阈值的回填算法,该算法在保证作业调度公平的同时提高了资源利用率。     

基于事件相关电位的水下机械手脑电波控制

为了解放水下机械手操作人员的双手,本文将脑-机接口(BCI)技术应用到水下机器人作业中,通过解析脑电信号并将其映射为具体指令从而控制机械手.现有的脑电波控制机械手方法在实时性、准确性方面无法满足实际的水下作业要求,提出了基于视觉诱发模式的ERP(事件相关电位)脑电信号来控制水下机械手的策略.通过融合脑电波控制与水下机械手作业的各自特点和优化ERP视觉诱发界面,使操作人员能够快速地完成给定任务.8位被试被邀请在建立的实验平台上进行控制实验,最终得到的辨识操作人员意图平均准确率、系统信息传输率与完成任务平均控制时间分别为91.5%、27.7 bits/min与90.1 s.与同类系统相比,本文所提控制策略系统性能更好,且作业效率满足实际作业要求.     

硬实时系统中基于软件容错模型的容错调度算法

在硬实时系统中,由于任务超时完成将会导致灾难性后果,因此硬实时系统必须具有实时性和可靠性保障.软件容错模型是提高硬实时系统容错能力的一种有效方法.针对硬实时系统中容错优先级两种分配策略存在的不足,基于软件容错模型提出了一种容错优先级可提升的双重优先级分配策略.该方法通过为替代版本分配双重优先级,不仅能够提高硬实时系统的容错能力,同时还能够显著减少任务间的抢占次数.为了获得双重优先级分配的最佳策略,基于任务最坏响应时间的可调度性分析,首先提出了一种最大的双重优先级配置搜索算法(MDPCSA).然后结合MDPCSA算法,提出了一种最优的双重优先级配置搜索算法(ODPCSA).仿真实验表明,与两种分配策略相比,在提高系统容错能力和降低抢占开销方面更为有效.     

一种可行的容错实时系统可调度性分析

针对容错实时系统中容错优先级两种分配策略存在的不足,通过对容错实时任务进行基于最坏响应时间的可调度性分析,提出了允许容错优先级降低的分配策略以提高系统的容错能力.经过深入的分析和实验证明,这种容错优先级的分配策略能够在以前两种分配策略无法提高系统容错能力的情况下,有效地提高系统的容错能力,设计并实现了改进的最佳容错优先级分配因子的搜索算法,并通过模拟实验进行了验证.     

一种面向BSP系统的多等待队列作业调度算法

在以往的BSP（Bulk Synchronous Parallel）系统中,作业调度都是采用基于单队列的优先级调度策略.它的优点是实现简单,但作业队列维护开销大,低优先级作业存在无限等待的问题.论文提出了面向BSP系统基于多等待队列的按优先级作业调度算法,以高响应比优先级队列为作业组织方式,并加入了作业优先级的动态调整策略,避免了低优先级作业因长期得不到执行而废弃的情况.目前,论文所提算法已成功运行于BC-BSP系统中.文中通过实验进一步证明,融合了作业优先级调整策略的基于多等待队列的作业调度算法较传统的单队列优先级调度算法在队列维护方面,能降低30％～50％的维护代价.另外,在兼顾作业的初始优先级的同时,能够减少低优先级作业的等待时间,避免低优先级作业的无限等待问题.     

一种基于YARN的高优先级作业调度实现方案

提交到YARN上的一个大数据作业会被切分为一个或者多个任务,任务是大数据作业申请资源和执行的基本单位[1]。在某些领域中存在需要对作业紧急度作有效区分使得高紧急度作业优先获得资源的需求,但是在现有的YARN资源调度策略中,对于提交到YARN上的高优先级作业缺乏资源优先分配和高质量的资源保障机制。本文在修改YARN原有资源调度方案的基础上,提出了一种基于YARN的高优先级作业调度实现方案。实验表明,提交到YARN上的高优先级作业执行效率提升了7%左右,证明设计方案行之有效。     

一种有限优先级的静态优先级分配算法

静态优先级调度在实时系统中得到了广泛应用.然而,静态优先级调度受到系统支持的优先级个数的限制.当任务的个数大于优先级个数时,需要将多个任务映射到同一个优先级.针对优先级个数有限的情况,给出了在截止期限大于周期时任务可调度的充分必要条件,并提出了基于有限优先级的静态优先级分配算法(AGP).AGP算法对于基本任务集合是最优的静态优先级分配算法.其最优性表现在,所需的优先级个数最小,并且若采用AGP算法不可调度某个任务集,则采用其他静态优先级分配算法也不可调度该任务集.模拟结果表明,AGP算法的可调度性要远远大于常量法.AGP算法对于解决在嵌入式实时系统中任务的优先级分配问题具有重要意义.     

一种基于多优先级队列和QoS的服务调度策略

针对网格服务流程的特点,在多维调度策略分析基础之上,提出基于多优先级队列和QoS的服务调度模型,并给出划分逻辑子网的思想,为具有不同需求的不同服务分配到最佳资源并得到最优处理.实验对资源调度公平性、服务请求响应时间等指标进行了测试,充分表明该调度模型的有效性.     

Operators׳ adaptation to imperfect automation – Impact of miss-prone alarm systems on attention allocation and performance

Operators in complex environments are often supported by alarm systems that indicate when to shift attention to certain tasks. As alarms are not perfectly reliable, operators have to select appropriate strategies of attention allocation to compensate for unreliability and to maintain overall performance. This study explores how humans adapt to differing alarm reliabilities. Within a multi-task simulation consisting of a monitoring task and two other concurrent tasks, participants were assigned to one of five groups. In the manual control group none of the tasks was supported by an alarm system, whereas the four experimental groups were supported in the monitoring task by a miss-prone alarm system differing in reliability, i.e. 68.75%, 75%, 87.5%, 93.75%. Compared to the manual control group, all experimental groups benefited from the support by alarms, with best performance for the highest reliability condition. However, for the lowest reliability group the benefit was associated with an increased attentional effort, a more demanding attention allocation strategy, and a declined relative performance in a concurrent task. Results are discussed in the context of recent automation research.     

A simulated study on the effects of information volume on traffic signs, viewing strategies and sign familiarity upon driver''s visual search performance

A two-stage simulation experiment was conducted to investigate the effect of information volume on traffic regulatory/road direction signs, drivers’ viewing strategies and sign familiarity on performance in visual search. In Stage I experiment, the amount of information on a total of 187 traffic regulatory and 1272 road direction signs was calculated and divided into five information levels using cluster analysis. In Stage II experiment, 24 subjects participated in a 2 (familiarity)×5 (information volume level)×2 (viewing strategy) mixed factorial experiment. Each subject was required to perform a visual search task and a question-and-answer (Q&A) task. Visual search time and number of correct responses collected serve as the objective dependent variables. Subjective workload related to time stress and visual effort was gathered through a modified three-point rating. Results show that information volume on traffic signs had significant impact on drivers’ visual search performance. Generally, the greater the amount of information, the slower the drivers in visual search are. However, while drivers had the highest accuracy rate in remembering purely pictorial traffic signs, these signs within the smallest information volume level required a relatively longer search time. Different viewing strategies also led to different performances. The back-and-forth strategy yielded better search performance than the fixed strategy. Subjective workload evaluation indicates that drivers with less sign familiarity will be under greater time/visual pressures. Guidelines for designing for traffic signs or in-vehicle signing systems are provided.

Relevance to industry

This study calculated the amount of information on traffic signs and compared the effects of different information volume on drivers’ visual search performance. The results can provide guidelines for traffic sign designers to help decide on the presentation format for in-vehicle signing information systems.     

Effects of design features of train electronic guidance interface on visual search,behavior, and usability

In urban rail trains, traditional printed guide information interfaces are being replaced by digital interfaces. An electronic guide screen is an important device for passengers to obtain information about the ride because the train is running underground. In particular, when the train is crowded, passengers must obtain information in advance and make appropriate decisions. Therefore, it is important to efficiently search for guidance interfaces. In this study, use scenarios of the guidance interface were simulated. The typical information layout and display mode in the current electronic guidance interface were the experimental variables. Through eye tracking and subjective evaluation, the effects of design features on user search performance, visual behavior, and usability satisfaction were discussed. The experimental results showed that the information layout and display mode of the guidance interface had an interactive effect on the task completion time, fixation counts, and usability score; they also had a significant effect on the recall accuracy and saccade ratio. Task completion time had a strong positive correlation with usability satisfaction and was correlated with visual behavior. The study confirmed that the split-screen display mode combined with interlaced layout could improve search performance and subjective satisfaction.Relevance to industryPrinted guide signs in subway cars are being replaced by electronic guide screens of different styles. Passengers must search for the required information within a limited period. In this study, the effects of different interface layouts and display modes on search performance, visual behavior, and usability were studied. This had a positive significance in improving user experience.     

基于任务分配与调度的GSAT算法求解3-SAT问题

基于不同分配策略的云计算任务调度以及任务分配与调度的主要目的,提出了一种新的算法—求解3-SAT问题的基于任务分配与调度的GSAT算法。该算法将3-SAT问题中的每一个变量形成一个任务,在GSAT算法的基础上,引入任务分配与调度指导贪心搜索;同时,在保留原有贪心搜索的前提下,根据任务分配与调度的思想和3-SAT问题的特点,设计了两种新的策略—分配策略和调度策略共同完成整个贪心搜索过程。以标准的SATLAB库中变量个数从 20～250的3 700个不同规模的标准Uniform Random 3-SAT 问题对新的算法的性能进行了合理的测试,并与高效和普通性能改进的GSAT算法的结果作了比较,结果表明,该算法具有更高的成功率和更少的翻转次数。     

Multi-Robot Task Allocation in Uncertain Environments

Multiple cooperating robots hold the promise of improved performance and increased fault tolerance for large-scale problems such as planetary survey and habitat construction. Multi-robot coordination, however, is a complex problem. We cast this problem in the framework of multi-robot dynamic task allocation under uncertainty. We then describe an empirical study that sought general guidelines for task allocation strategies in multi-robot systems. We identify four distinct task allocation strategies, and demonstrate them in two versions of the multi-robot emergency handling task. We describe an experimental setup to compare results obtained from a simulated grid world to those obtained from physical mobile robot experiments. Data resulting from eight hours of experiments with multiple mobile robots are compared to the trend identified in simulation. The data from the simulations show that there is no single strategy that produces best performance in all cases, and that the best task allocation strategy changes as a function of the noise in the system. This result is significant, and shows the need for further investigation of task allocation strategies and their application to planetary exploration.     

基于蒙特卡罗贝叶斯推理的移动群智感知可靠任务分配机制

针对现有任务分配策略的不足,研究了在工人数量有限的移动群智感知系统中任务分配策略,借助社交网络来分配任务并获得高收益。首先,建立了社交网络的动态不确定环境,利用社交网络完成任务,传播任务。然后考虑到不同社交网络对任务的偏好不同,设置任务偏好度这一不确定指标,借助经济学风险价值的理论描述任务分配的可靠性。最后利用蒙特卡罗贝叶斯推理方法研究任务动态传播模型的复杂参数的高斯过程,设计基于知识梯度的采样算法选择蒙特卡罗采样点,从而实现高收益的任务分配方案。为了验证所提策略的性能,将其与四种基准的采样算法进行比较。实验结果表明,所提任务分配策略在提高收益方面是有效的。     

Dynamic scheduling using a pheromone-based approach in multi-agent systems

The scheduling problems in factory domain applications usually involve many parallel machines, with each machine capable of processing several tasks. In most cases, changing the current machine state to another state to process a different task incurs additional material costs and time. If the overall system can maintain the expected performance, minimizing these state changes is very beneficial, and agent-based approaches inspired by the task allocation strategies of several social insects have gained increasing attention as solutions. The basic concept is based on the stimulus-threshold relation, and an individual agent determines whether it performs a given task or not based on two sets of terms, the environmental external stimuli for the task and the internal threshold values of all possible tasks. In this approach, selecting appropriate threshold values is directly related to the overall system performance, and we present a pheromone-based approach to obtain appropriate threshold values. Each agent maintains a limited, constant-sized task history queue of recently processed tasks, and the information of each agent is individually used to calculate the threshold values of tasks. Based on various experimental results, we show that the performance of the proposed method is comparable to those of other conventional methods.     

Operator visual attention allocation prediction in a robotic arm teleoperation interface

In digital interactive interfaces with high visual workloads, it is important for operators to allocate their limited attentional resources appropriately to ensure efficient information collection. The salience, effort, expectancy, value (SEEV) model, which combines top-down and bottom-up attention mechanisms for predicting attention allocation, has been validated in research areas such as piloting, driving, and surgical operations. However, the validity of the SEEV model in the field of robotic arm teleoperation has not yet been thoroughly studied. The primary purpose of this study was to confirm the feasibility of the SEEV model for operator visual attention allocation prediction in a robotic arm teleoperation scenario. The improved ITTI algorithm, distance-measuring tool, Delphi method, and lowest ordinal algorithm were adopted to qualify the four factors of the SEEV model, which also contributed to salience and expectancy quantification methods. Accordingly, an attention allocation prediction model in a robotic arm teleoperation scene was constructed. To verify the validity of the prediction model, 20 participants were recruited to control the robotic arm using V-REP simulation software, and their fixation durations were recorded using an eye tracker as an attention allocation indicator. Participants controlled the robotic arm according to the experimental requirements and operational tasks, such as grasping and placing the target. The results demonstrated that the theoretical data based on the SEEV prediction model are significantly related to the proportion of fixation durations. The experiment verifies the suitability of the SEEV prediction model, and it is anticipated to be utilized in the optimization of interactive interfaces for robotic arm teleoperation.     

Search Strategies for Multiple UAV Search and Destroy Missions

Multiple UAVs are deployed to carry out a search and destroy mission in a bounded region. The UAVs have limited sensor range and can carry limited resources which reduce with use. The UAVs perform a search task to detect targets. When a target is detected which requires different type and quantities of resources to completely destroy, then a team of UAVs called as a coalition is formed to attack the target. The coalition members have to modify their route to attack the target, in the process, the search task is affected, as search and destroy tasks are coupled. The performance of the mission is a function of the search and the task allocation strategies. Therefore, for a given task allocation strategy, we need to devise search strategies that are efficient. In this paper, we propose three different search strategies namely; random search strategy, lanes based search strategy and grid based search strategy and analyze their performance through Monte-Carlo simulations. The results show that the grid based search strategy performs the best but with high information overhead.     

The impact of distraction mitigation strategies on driving performance

OBJECTIVES: An experiment was conducted to assess the effects of distraction mitigation strategies on drivers' performance and productivity while engaged in an in-vehicle information system task. BACKGROUND: Previous studies show that in-vehicle tasks undermine driver safety and there is a need to mitigate driver distraction. METHOD: An advising strategy that alerts drivers to potential dangers and a locking strategy that prevents the driver from continuing the distracting task were presented to 16 middle-aged and 12 older drivers in a driving simulator in two modes (auditory, visual) and two road conditions (curves, braking events). RESULTS: Distraction was a problem for both age groups. Visual distractions were more detrimental than auditory ones for curve negotiation, as depicted by more erratic steering, F (6, 155) = 26.76, p < .05. Drivers did brake more abruptly under auditory distractions, but this effect was mitigated by both the advising, t (155) = 8.37, p < .05, and locking strategies, t (155) = 8.49, p < .05. The locking strategy also resulted in longer minimum time to collision for middle-aged drivers engaged in visual distractions, F (6, 138) = 2.43, p < .05. CONCLUSIONS: Adaptive interfaces can reduce abrupt braking on curve entries resulting from auditory distractions and can also improve the braking response for distracted drivers. APPLICATION: These strategies can be incorporated into existing in-vehicle systems, thus mitigating the effects of distraction and improving driver performance.