一种基于DAG的并行系统任务调度方法

设计了一种适用于同构总线式多核环境的任务调度算法,着重优化了传统静态列表算法中对于任务节点等级较为粗糙的计算方式,并改善了对通信的调度。通过统计性调度实验,表明该任务调度算法相比传统的调度方法具有一定的优化效果。     

1553B总线组网研究

论文介绍了航空总线MIL-STD-1553B严格实时、高可靠的突出特点,并对总线标准中与其对应的针对性设计的基本结构和基本运作原理进行了分析,讨论了总线系统设计中除底层RT、BC、MT终端设计外的两个网络级核心问题：总线拓扑和总线控制。     

实时网络的分布式调度

针对主—从结构实时网络的性能特点,提出了一种基于EDF的主节点分布式实时任务调度算法,给出了该调度算法下实时任务组的可调度的充分条件。仿真测试表明,该调度算法满足实时约束,适合于主—从结构的实时网络调度。     

基于1553B总线的接口实现与测试

在深入研究1553B总线协议和总线实现方式的基础上,通过以BU-61580协议芯片为核心设计了原理样机的软硬件系统,原理样机实现了1553B总线协议终端的功能,并结合总线测试卡进行了功能测试。测试结果表明,数据在1553B总线上传输正常,原理样机实现了其BC和RT的全部功能,满足MIL-STD-1553B总线协议的要求。     

基于ARM9的1553B与CAN总线转换卡的设计与实现

在某些军用测控系统中,经常存在1553B总线与CAN总线之间的总线转换,这就促使了1553B与CAN总线转换卡的诞生。本文1553B与CAN总线转换卡采用ARM9处理器作为中间转换平台,RTLinux操作系统作为调度,通过上层应用程序实现了1553B总线与CAN总线之间的信息转换。转换卡还通过扩展的LCD接口和串口,实现了转换数据的实时监控。该系统在实际应用中得到了实时性,可靠性等方面的验证。     

浅析高速1553B总线控制器通信管理系统设计

1553B总线全称为数字时分命令/响应型多路传输数据总线,随着计算机技术的发展,该总线技术开始在各行各业得到了广泛的应用.本文基于此,以高速1553B总线控制器通信过程为切入点,首先分析了高速1553B总线控制器通信原理及特点,然后基于双缓冲机制设计了高速1553B总线控制器通信管理系统的总线控制器(BC)和远程终端(RT)两个部分,希望能为相关人员提供些许参考价值.     

基于SM61580的MIL-STD-1553B总线终端设计

通过对MIL-STD-1553B总线的研究,实现远程终端(RT)与总线控制器(BC)之间高效、可靠的数据通信,提出了一种基于SM61580的MIL-STD-1553B总线终端设计方案。选用SM61580芯片,利用SM7C133存储功能,并结合MSP430F247的控制优势,采用透明模式连接芯片与处理器,实现1553B总线终端设计。该1553B总线终端系统的应用具有普遍的实用性。     

基于1553B总线的嵌入式网络BBC设计与实现

文章介绍了1553B总线的特点,基于1553总线设计的嵌入式网络节点类型和网络结构。为实现嵌入式网络总线控制器的双机冗余,设计了备份总线控制器BBC,重点对BBC的工作方式选择和程序实现进行阐述。     

1553B总线控制器双机热备份设计

1553B总线作为一种高可靠的总线技术,广泛应用运用于军事领域。由于1553B总线双冗余备份的只是总线传输通道,而总线上的控制器没有热备份,一旦总线控制器出现故障,则整个总线将瘫痪。主要论述一种利用软件实现总线控制器的双机热备份设计思想和方法,此方法易于实现,效率很高,并有效地防止了工作BC和备用BC的误切换,实践验证,这种设计切实可行,有一定的通用性。     

提高1553B总线通信装置可靠性方法的研究

1553B总线具有传输速率高、可靠性高、实时性好等优点,在国内航空、航天等领域中均大量使用1553B总线,但实际应用中的1553B总线缺少可靠性设计指导,为了提高总线通信装置总线可靠性,针对1553B总线通信的特点,提出两种设计方法来提高通信可靠性,分别是在系统连接模式上采用双BC控制端冗余结构和在应用层协议建立矢量字访问机制来提高通信装置可靠性,运用上述方法能有效的提高总线的性能和可靠性,为国防装备项目应用1553B总线时提供可靠性设计参考。     

Resource scheduling in mobile edge computing using improved ant colony algorithm for space information network

With the development of space information network (SIN), new network applications are emerging. Satellites are not only used for storage and transmission but also gradually used for calculation and analysis, so the demand for resources is increasing. But satellite resources are still limited. Mobile edge computing (MEC) is considered an effective technique to reduce the pressure on satellite resources. To solve the problem of task execution delay caused by limited satellite resources, we designed Space Mobile Edge Computing Network (SMECN) architecture. According to this architecture, we propose a resource scheduling method. First, we decompose the user tasks in SMECN, so that the tasks can be assigned to different servers. An improved ant colony resource scheduling algorithm for SMECN is proposed. The heuristic factors and pheromones of the ant colony algorithm are improved through time and resource constraints, and the roulette algorithm is applied to route selection to avoid falling into the local optimum. We propose a dynamic scheduling algorithm to improve the contract network protocol to cope with the dynamic changes of the SIN and dynamically adjust the task execution to improve the service capability of the SIN. The simulation results show that when the number of tasks reaches 200, the algorithm proposed in this paper takes 17.52% less execution time than the Min-Min algorithm, uses 9.58% less resources than the PSO algorithm, and achieves a resource allocation rate of 91.65%. Finally, introducing dynamic scheduling algorithms can effectively reduce task execution time and improve task availability.     

Network real-time scheduling algorithm based on multi-feature dynamic priority

Real-time task scheduling system structure and task model were proposed aiming at the network real-time scheduling problem.The task degree of urgency was defined by considering the deadline of task,execution time and interval time between works.The task degree of tightness was proposed based on service-level assurance,according to functional importance of different tasks in the real-time task scheduling system.The thrashing limit for avoiding task switching frequently was acquired through dynamic regulation to task priorities by degree of urgency and degree of tightness,which guaranteed the success rate of tasks execution and utilization ratio of client execution.Test simulation results suggest that the multi-feature dynamic priority scheduling strategy improves the success rate of task scheduling and shorten the average response time,which suggests it has obvious superiority compared with BE and EDF scheduling algorithm.     

一种基于风险感知策略的多节点任务调度方法

为解决无人机(UAV)集群任务调度时面临各节点动态、不稳定的情况,该文提出一种面向多计算节点的可尽量避免任务中断且具有容错性的任务调度方法。该方法首先为基于多计算节点构建了一个以最小化任务平均完成时间为优化目标的任务分配策略;然后基于任务的完成时间和边缘计算节点的存留时间两者的概率分布,将任务计算节点上的执行风险量化成额外开销时间;最后以任务的完成时间与额外开销时间之和替换原本的完成时间,设计了风险感知的任务分配策略。在仿真环境下将该文提出的任务调度方法与3种基准调度方法进行了对比实验,实验结果表明该方法能够有效地降低任务平均响应时间、任务平均执行次数以及任务截止时间错失率。证明该文提出的方法降低了任务重调度和重新执行带来的额外开销,可实现分布式协同计算任务的调度工作,为复杂场景下的无人机集群网络提供新的技术支持。     

Layout conscious approach and bus architecture synthesis for hardware/software codesign of systems on chip optimized for speed

This paper presents a layout-conscious approach for hardware/software codesign of systems-on-chip (SoCs) optimized for latency, including an original algorithm for bus architecture synthesis. Compared to similar work, the method addresses layout related issues that affect system optimization, such as the dependency of task communication speed on interconnect parasitic. The codesign flow executes three consecutive steps: 1) combined partitioning and scheduling: besides partitioning and scheduling, this step also identifies the minimum speed constraints for each data link; 2) IP core placement, bus architecture synthesis, and routing: IP cores are placed using a hierarchical cluster growth algorithm; bus architecture synthesis identifies a set of possible building blocks and then assembles them for minimizing bus length and complexity; poor solutions are pruned using a special table structure and select-eliminated method; and 3) rescheduling for the best bus architecture. This paper offers extensive experiments for the proposed codesign method, including bus architecture synthesis for a network processor and a JPEG SoC.     

A non‐cooperative game model for reliability‐based task scheduling in cloud computing

Cloud computing is a newly emerging distributed system. Task scheduling is the core research of cloud computing which studies how to allocate the tasks among the physical nodes, so that the tasks can get a balanced allocation or each task's execution cost decreases to the minimum, or the overall system performance is optimal. Unlike task scheduling based on time or cost before, aiming at the special reliability requirements in cloud computing, we propose a non‐cooperative game model for reliability‐based task scheduling approach. This model takes the steady‐state availability that computing nodes provide as the target, takes the task slicing strategy of the schedulers as the game strategy, then finds the Nash equilibrium solution. We also design a task scheduling algorithm based on this model. It can be seen from the experiments that our task scheduling algorithm is better than the so‐called balanced scheduling algorithm.     

基于价值优化的相控阵雷达任务调度算法

针对相控阵雷达时间资源分配问题,该文提出一种基于价值优化的任务调度算法。首先建立任务调度属性参数,对跟踪任务队列进行可行性分析和筛选操作,确定跟踪任务调度属性。其次,根据任务最大价值及其变化斜率,建立关于实际执行时刻的动态任务价值函数,并基于此构建任务调度的价值优化模型,对跟踪任务执行时刻进行分配,以更好满足及时性原则。最后,利用执行跟踪任务间的空闲时间片对搜索任务进行调度。仿真结果表明,该文算法有效减小了时间偏移量,提升了实现价值率。     

多功能组网雷达可变参数任务规划方法

针对任意周期雷达任务(侦查、干扰、探测等)在多功能组网雷达中的规划问题,提出了一种可变参数的任务规划方法。首先,分析雷达任务特性,建立可变参数雷达任务模型。然后,设定组网雷达中各雷达任务规划时间窗宽度和开槽宽度,使组网雷达可执行任务的周期与现有任务周期最接近。接着,针对雷达任务任意周期的特点,以任务周期变化量最小为原则对任务周期进行调整,保证多个任务在同一部雷达中不重叠,并且具有周期性。最后,利用启发式算法,以任务驻留时间的平均隶属度最大为目标完成任务规划。仿真结果与实例证明了该方法的有效性。     

Run-time management of systems with partially reconfigurable FPGAs

Partial reconfiguration (PR) of FPGAs can be used to dynamically extend and adapt the functionality of computing systems by swapping in and out HW tasks. To coordinate the on-demand task execution, we propose and implement a Run-Time System Manager (RTSM) for scheduling software (SW) tasks on available processor(s) and hardware (HW) tasks on any number of reconfigurable regions (RRs) of a partially reconfigurable FPGA. Fed with the initial partitioning of the application into tasks, the corresponding task graph, and the available task mappings, the RTSM controls system operation considering the status of each task and region (e.g. busy, idle, scheduled for reconfiguration/execution, etc). Our RTSM supports task reuse and configuration prefetching to minimize reconfigurations, task movement among regions to efficiently manage the FPGA area, and region reservation for future reconfiguration and execution. We validate the correctness and portability of our RTSM executing an image processing application on two Xilinx-based platforms: ZedBoard and XUPV5. We also perform a more extensive evaluation of its features using a simulation framework, and find that – despite the technology limitations – our approach can give promising results in terms of scheduling quality. Since our RTSM supports also the scheduling of parallel SW tasks, we use it to manage the execution of the entire parallel Edge Detection application on a desktop; we compare the application execution time with that using the OpenMP framework and find that with our RTSM execution is 2.4 times faster than the unoptimized OpenMP version. When processor affinity optimization is enabled for OpenMP, our RTMS and the OpenMP are on par, indicating that the scheduling efficiency of our RTSM is competitive to this state-of-the-art scheduler, while supporting in addition the management of HW tasks.     

大规模网络管理中的任务分解与调度

集中式的管理模式和简单的基于移动agent的网络管理方法都已不能满足大型网络管理的需要,为此,在给出基于多agent的网络管理框架的基础上,提出了一种基于任务依赖关系的任务分解算法,把网络管理任务分解为具有不同优先级的子任务,处于同一优先层次的子任务可以并行执行,根据子任务的优先级产生结合网络管理特点的调度策略,理论分析和实验表明:在大规模网络管理中采用任务分解技术能够提高时间效率和减轻网络负载。     

Energy Efficient Real-Time Task Scheduling for Embedded Systems with Hybrid Main Memory

Available energy becomes a critical design issue for the increasingly complex real-time embedded systems. Phase Change Memory (PCM), with high density and low idle power, has recently been extensively studied as a promising alternative of DRAM. Hybrid PCM-DRAM main memory architecture has been proposed to leverage the low power of PCM and high speed of DRAM. In this paper, we propose energy-aware real-time task scheduling strategies for hybrid PCM-DRAM based embedded systems. Given the execution time variation when a task is loaded into PCM or DRAM, we re-design the static table-driven scheduling for a set of fixed tasks, as well as the Rate-Monotonic (RM) and Earliest Deadline First (EDF) scheduling policies for periodic task sets. Furthermore, since the actual execution time can be much shorter than the worst-case execution time in the actual execution, we propose online schedulers which migrates the tasks between PCM and DRAM to optimize the energy consumption by utilizing the slack time resulted from the completed tasks. All the proposed algorithms minimize the number of task migrations from PCM to DRAM by ensuring that aperiodic tasks are not migrated while each periodic task instance can be migrated at most once. Experimental results show our proposed scheduling algorithms satisfy the real-time constraints and significantly reduce the energy consumption.