基于动态松弛时间回收的开销敏感节能实时调度算法

为适应实际系统中任务集的不断变化以及不可忽视状态切换开销的要求,针对多核多处理器系统中常见的周期任务模型,提出一种基于动态松弛时间回收的开销敏感节能实时调度算法DSROM,在每个TL面的初始时刻、任务提前完成时刻实现节能调度及动态松弛时间回收,在不违反周期任务集可调度性的基础上,达到实时约束与能耗节余之间的合理折衷。模拟实验结果表明,DSROM算法不仅保证了周期任务集的最优可调度性,而且当任务集总负载超过某一个值后,其节能效果整体优于现有方法,最多可节能近20%。     

面向安全关键实时应用的分层防危调度算法研究

针对现有防危调度算法在软硬件失效情况下防危能力不足的问题,具体进行了以下工作:构建了一种分层防危实时调度模型,该模型从功能组件和安全分区两方面描述了安全关键实时应用的防危性需求,并给出一种基于分层调度思想的三级防危调度器框架。以该模型和框架为基础,提出了一种新的分层防危调度算法(HSS),该算法对安全关键实时应用中不同关键度的功能组件采用空间隔离机制,对同一功能组件内的不同分区采用时间隔离机制,兼顾实现了时空隔离的防危效果。仿真实验结果表明,HSS算法与其他同类算法相比,在防危效果和应用负载承受能力方面具有较好的表现。     

一种新型实时调度算法研究

在许多片上特定应用系统中，任务多且切换频繁，任务切换开销大，有时甚至严重影响系统的可调度性．研究了动态可抢占门限调度算法，它通过初始门限值、动态门限值的计算和优化线程分配，实现了在处理器高利用率下，有效降低任务切换开销的目的，并相应地减少了对内存的需求．动态可抢占门限调度算法是将静态抢占门限算法与动态调度算法有机地结合在一起。完成了由静态到动态无缝转换．     

面向分布式实时系统的安全驱动调度算法研究

针对现有实时调度算法无法适应动态安全需求的问题,构建了一种安全驱动调度模型,该模型从系统安全级别、系统安全服务和任务安全策略三个方面描述了实时系统的动态安全需求,并设计了一种基于安全驱动的实时任务调度器框架。以该模型和框架为基础,提出了一种安全驱动调度算法(Security Driven Scheduling Algorithm,SDSA)。从全局角度对新到达任务进行可调度性检查,并将可调度任务分配到合适的处理机上运行。按照系统安全级别来动态调整已分配到各处理机上实时任务的安全策略,使其达到安全性和可调度性的最优平衡。采用优先级抢占式策略对各实时任务进行调度。仿真结果表明,SDSA算法与其他同类算法相比,在系统动态安全需求的适应性、关键任务的可调度性以及安全防危能力等方面具有较好的表现。     

嵌入式Linux实时调度算法及应用

针对Linux2.6内核在嵌入式应用中实时性不足的问题,提出了自适应实时调度算法,并应用它构建了嵌入式Linux远程图像实时监控系统.调度算法在O(1)调度性能的基础上,为实时进程增加了截止期、带宽(即利用率,执行时间与其周期的比值)等属性,设计了实时进程插入、时钟中断、实时进程接受及带宽调节等函数,实时进程的带宽、时间片可以自适应改变.实验结果表明,该算法改善了任务的中断响应时间和上下文切换时间.     

一种MapReduce实时调度算法设计及实现

MapReduce是云计算中重要的批数据处理框架,多任务共享MapReduce机群并满足任务实时性要求是调度算法急需解决的问题。提出两阶段实时调度算法,将调度划分为任务间调度和任务内调度。对于任务间调度,使用抽样法和经验值法确定子任务执行时间,利用该参数建立资源分配模型,动态确定任务优先级进行调度;对于子任务使用延迟调度策略进行调度,保证计算的本地性。实验结果显示,两阶段实时调度算法相比公平调度算法和FIFO算法,在保证吞吐量的同时能够满足任务实时性要求。     

OPC实时任务系统动态调度算法的研究与设计

本文基于已有的OPCServer实时任务模型,设计了处理混合任务集的动态调度算法(基于截止期优先)和实现方式。该算法实现了对混合任集可调度性的判断,可以完成有硬实时性要求的非周期性任务和周期性任务的调度,并给出了相应的调度结果。     

通用调度框架的改进及其在Linux中的实现

在嵌入式Linux实时系统中,要求内核对不同时问约束的任务采用不同的调度算法.但目前Linux内核采用单一的实时调度模式,不能灵活地执行多种调度算法,也就无法满足实时系统中实时任务的时间约束.引入了一种能够在Linux内核调度中执行多种调度算法的框架,即通用调度框架(GSF),并改进了其中的多算法调用机制,从而更好地在Linux内核中实现GSF.     

开销敏感的多处理器最优节能实时调度算法

嵌入式多处理器系统的能耗问题变得日益重要,如何减少能耗同时满足实时约束成为多处理器系统节能实时调度中的一个重要问题.目前绝大多数研究基于关键速度降低处理器的频率以减少动态能耗,采用关闭处理器的方法减少静态能耗.虽然这种方法可以实现节能,但是不能保证最小化能耗.而现有最优的节能实时调度未考虑处理器状态切换的时间和能量开销,因此在切换开销不可忽视的实际平台中不再是最优的.文中针对具有独立动态电压频率调节和动态功耗管理功能的多处理器系统,考虑处理器切换开销,提出一种基于帧任务模型的最优节能实时调度算法.该算法根据关键速度来判断系统负载情况,确定具有最低能耗值的活跃处理器个数,然后根据状态切换开销来确定最优调度序列.该算法允许实时任务在处理器之间任意迁移,计算复杂度小,易于实现.数学分析证明了该算法的最优性.     

基于PTIDES执行策略的调度算法

分析现有PTIDES执行策略调度算法,综合考虑事件的截止期和执行时间,改进传统最小空闲时间优先算法,将空闲时间作为事件调度优先权,提出零空闲时间优先PTIDES调度算法——ZSFPTIDES。实例分析表明,ZSFPTIDES调度算法能避免事件在处理过程中因得不到及时处理而夭折的现象,减小事件的抢占切换率,优化分布实时嵌入式系统的调度性能。     

Rolling-horizon scheduling for energy constrained distributed real-time embedded systems

Energy-efficient scheduling approaches are critical to battery driven real-time embedded systems. Traditional energy-aware scheduling schemes are mainly based on the individual task scheduling. Consequently, the scheduling space for each task is small, and the schedulability and energy saving are very limited, especially when the system is heavily loaded. To remedy this problem, we propose a novel rolling-horizon (RH) strategy that can be applied to any scheduling algorithm to improve schedulability. In addition, we develop a new energy-efficient adaptive scheduling algorithm (EASA) that can adaptively adjust supply voltages according to the system workload for energy efficiency. Both the RH strategy and EASA algorithm are combined to form our scheduling approach, RH-EASA. Experimental results show that in comparison with some typical traditional scheduling schemes, RH-EASA can achieve significant energy savings while meeting most task deadlines (namely, high schedulability) for distributed real-time embedded systems with dynamic workloads.     

Real-time task scheduling and network device security for complex embedded systems based on deep learning networks

As a hotspot of machine learning research, deep learning is applied in many fields. Embedded systems are becoming more and more complex and networked, so the real-time performance of embedded systems and the security of network embedded devices face severe challenges. Based on this, this paper studies the real-time task scheduling problem for complex embedded systems and the security of embedded network devices. For real-time, this paper proposes a comprehensive task scheduling algorithm. Based on the task classification in the embedded system, different scheduling methods are adopted for different tasks, and the scheduling mode is flexibly changed as the system load changes. A dynamic integrity measurement model is established based on the star trust chain structure, and the hardware implementation mechanism of constructing dynamic trust chain in embedded system is studied. The dynamic reconfigurable hardware design method based on FPGA is applied to the construction of dynamic trust chain, and a verification system is designed to verify the dynamic measurement mechanism. This can solve the security problem of deep network embedded devices to a certain extent.     

一种提高构件化嵌入式操作系统性能的方案

本文分析了现有构件化嵌入式操作系统所用调度算法存在的缺点,提出抢占阈值调度算法是更为合适的算法。通过仿真实验比较抢占阈值调度算法、非抢占式调度算法和FIFO(First-In-First-Out)调度算法的性能,证明了上述结论。通过分析现有嵌入式系统构件模型的特点,提出了一种构件模型以及将构件映射成任务的方式,还提出了一种设计方法。整个方案能提高构件化嵌入式操作系统的性能。     

多核系统中基于Global EDF 的在线节能实时调度算法

随着多核系统能耗问题日益突出,在满足时间约束条件下降低系统能耗成为多核实时节能调度研究中亟待解决的问题之一.现有研究成果基于事先已知实时任务属性的假设,而实际应用中,只有当任务到达之后才能够获得其属性.为此,针对一般任务模型,不基于任何先验知识提出一种多核系统中基于Global EDF在线节能硬实时任务调度算法,通过引入速度调节因子,利用松弛时间,结合动态功耗管理和动态电压/频率调节技术,降低多核系统中任务的执行速度,达到实时约束与能耗节余之间的合理折衷.所提出的算法仅在上下文切换和任务完成时进行动态电压/频率调节,计算复杂度小,易于在实时操作系统中实现.实验结果表明,该算法适用于不同类型的片上动态电压/频率调节技术,节能效果始终优于Global EDF算法,最多可节能15％～20％,最少可节能5％～10％.     

一种同构多处理机动态实时调度算法

本文提出一种新型线性复杂度多处理机实时任务启发式调度算法,利用并行技术为动态实时系统提供较优解．使用大量存在可行调度的任务集合测试多处理机实时任务调度算法的性能,分析了几种主要参数对调度成功率的影响．实验表明新调度算法调度成功率较高,适用于不完全知晓任务参数的动态多处理机实时系统．     

A Feasibility Decision Algorithm for Rate Monotonic and Deadline Monotonic Scheduling

Rate monotonic and deadline monotonic scheduling are commonly used for periodic real-time task systems. This paper discusses a feasibility decision for a given real-time task system when the system is scheduled by rate monotonic and deadline monotonic scheduling. The time complexity of existing feasibility decision algorithms depends on both the number of tasks and maximum periods or deadlines when the periods and deadlines are integers. This paper presents a new necessary and sufficient condition for a given task system to be feasible and proposes a new feasibility decision algorithm based on that condition. The time complexity of this algorithm depends solely on the number of tasks. This condition can also be applied as a sufficient condition for a task system using priority inheritance protocols to be feasible with rate monotonic and deadline monotonic scheduling.     

实时性分布嵌入式系统设计

分布嵌入式系统的应用通常具有实时性要求，其实时性需要从任务调度、通信协议、调用接口和嵌入式操作系统四个方面得到支持。采用两阶段调度策略既可以保证调用的透明性，又可以简化任务调度算法；基于优先级的线路竞争算法可以改进以太网使其符合实时性要求；采用微型Java虚拟机作为分布式中间件可以为系统调用接口提供一个统一的支持平台。     

UC／OS-II操作系统内核的改进

UC／OS—II是一种针对嵌入式设计的实时多任务操作系统，采用基于优先级的占先式任务调度算法，虽然效率高但比较单调。在实现TCP/IP协议中，这种内核调度方法对Intemet服务进程显得不适应。本文分析了UC／OS—II和Linux操作系统内核任务调度算法，在此基础上提出了一种改进UC／OS-II内核的方法，使其更适合于在嵌入式中实现Intemet服务。     

Real-Time Transaction Scheduling: A Framework for Synthesizing Static and Dynamic Factors

Real-time databases are poised to be an important component of complex embedded real-time systems. In real-time databases (as opposed to real-time systems), transactions must satisfy the ACID properties in addition to satisfying the timing constraints specified for each transaction (or task). Although several approaches have been proposed to combine real-time scheduling and database concurrency control methods, to the best of our knowledge, none of them provide a framework for taking into account the dynamic cost associated with aborts, rollbacks, and restarts of transactions. In this paper, we propose a framework in which both static and dynamic costs of transactions can be taken into account. Specifically, we present: i) a method for pre-analyzing transactions based on the notion of branch-points for data accessed up to a branch point and predicting expected data access to be incurred for completing the transaction, ii) a formulation of cost that includes static and dynamic factors for prioritizing transactions, iii) a scheduling algorithm which uses the above two, and iv) simulation of the algorithm for several operating conditions and workload. Our dynamic priority assignment policy (termed the cost conscious approach or CCA) adapts well to fluctuations in the system load without causing excessive numbers of transaction restarts. Our simulations indicate that i) CCA performs better than the EDF-HP algorithm for both soft and firm deadlines, ii) CCA is more fair than EDF-HP, iii) CCA is better than EDF-CR for soft deadline, even though CCA requires and uses less information, and iv) CCA is especially good for disk-resident data.