调度和拥塞控制相结合的无线网络资源分配模型

研究了基于WLAN访问Internet的网络基站处流,提出了一种基于队列长度的调度方法和基于信道容量的拥塞控制模式,以达到网络资源的公平分配,并解决由于不恰当处理基站处堆积数据包而引起的弊端。在提出的资源分配模型中,调度算法根据各条流堆积的队列长度来随机地选择将要发送的数据分组;而拥塞控制模式中,将链路使用率作为拥塞指示,通过计算,平等地反馈给每一条流的发送端。发送端根据反馈到的拥塞信息来调整发送速率,以达到资源分配的公平性。仿真的结果表明：各条流能公平地共享无线网络的带宽。此算法的最大的优点在于基站不需要按照某种特定的公平性定义来选择数据包却能达到很高的公平性。     

Minimizing migrations in fair multiprocessor scheduling of persistent tasks

Suppose that we are given n persistent tasks (jobs) that need to be executed in an equitable way on m processors (machines). Each machine is capable of performing one unit of work in each integral time unit and each job may be executed on at most one machine at a time. The schedule needs to specify which job is to be executed on each machine in each time window. The goal is to find a schedule that minimizes job migrations between machines while guaranteeing a fair schedule. We measure the fairness by the drift d defined as the maximum difference between the execution times accumulated by any two jobs. As jobs are persistent we measure the quality of the schedule by the ratio of the number of migrations to time windows. We show a tradeoff between the drift and the number of migrations. Let n = qm + r with 0 < r < m (the problem is trivial for n ≤ m and for r = 0). For any d ≥ 1, we show a schedule that achieves a migration ratio less than r(m − r)/(n(q(d − 1)) + ∊ > 0; namely, it asymptotically requires r(m − r) job migrations every n(q(d − 1) + 1) time windows. We show how to implement the schedule efficiently. We prove that our algorithm is almost optimal by proving a lower bound of r(m − r)/(nqd) on the migration ratio. We also give a more complicated schedule that matches the lower bound for a special case when 2q ≤ d and m = 2r. Our algorithms can be extended to the dynamic case in which jobs enter and leave the system over time.     

一种新型的网络包公平调度算法的研究*

针对现有分组轮转法的局限,提出一种新的分组策略——虚拟权重队列分组策略。在这个新的分组策略的基础上,结合DRR和WF2Q,提出了虚拟权重队列分组轮转法。仿真实验表明,虚拟权重队列分组轮转调度算法比现有的分组轮转法拥有更好的延时性能和公平性能。     

多处理器系统的实时调度算法研究

调度算法是实时系统的关键技术,选取何种算法调度实时任务,这将直接影响着系统的实时响应能力。多处理器系统有局部调度和全局调度两类实时调度方法,以PFair公平调度为代表的全局调度是当前研究的热点。研究了典型局部调度EDF-FF算法和典型PFair公平调度PD^2算法,比较了多处理器系统采用PD^2算法相对于采用EDF-FF算法实现任务调度的优点,分析了由于任务频繁抢占和迁移,PD^2算法引起的时间消耗,估计并比较了PD2算法和EDF-FF算法的时间消耗,最后得出结论：在共享内存的多处理器系统中,公平调度算法是实时任务调度的比较理想的选择。     

基于无线传感器网络的分布式时分多址调度策略

针对周期汇报型无线传感器网络(WSN)中数据量大而导致的无线信号冲突概率高的问题,提出了一种分布式的时分多址调度策略(DTSS)。该策略采用了一种分布式的竞争算法来构建节点的时隙调度表,即每个节点根据自身搜集到的信息来决定下一跳目的节点,并和其他节点竞争传输时隙。所有节点完成时隙调度表的建立后,节点在每个数据采集周期根据自己的工作时隙调度表发送和接收数据。仿真结果表明,该策略避免了节点无线信号的冲突,降低了节点能耗,延长了网络生命周期。     

An optimal boundary fair scheduling algorithm for multiprocessor real-time systems

With the emergence of multicore processors, the research on multiprocessor real-time scheduling has caught more researchers’ attention recently. Although the topic has been studied for decades, it is still an evolving research field with many open problems. In this work, focusing on periodic real-time tasks with quantum-based computation requirements and implicit deadlines, we propose a novel optimal scheduling algorithm, namely boundary fair (Bfair), which can achieve full system utilization as the well-known Pfair scheduling algorithms. However, different from Pfair algorithms that make scheduling decisions and enforce proportional progress (i.e., fairness) for all tasks at each and every time unit, Bfair makes scheduling decisions and enforces fairness to tasks only at tasks’ period boundaries (i.e., deadlines of periodic tasks). The correctness of the Bfair algorithm to meet the deadlines of all tasks’ instances is formally proved and its performance is evaluated through extensive simulations. The results show that, compared to that of Pfair algorithms, Bfair can significantly reduce the number of scheduling points (by up to 94%) and the overhead of Bfair at each scheduling point is comparable to that of the most efficient Pfair algorithm (i.e., PD²). Moreover, by aggregating the time allocation of tasks for the time interval between consecutive period boundaries, the resulting Bfair schedule can dramatically reduce the number of required context switches and task migrations (as much as 82% and 85%, respectively) when compared to those of Pfair schedules, which in turn reduces the run-time overhead of the system.     

面向温度优化的片上网络任务调度方法

随着片上网络规模的扩大和研究的逐步深入,如何将芯片上众多的任务进行合理的调度成为系统温度优化的关键之一。针对片上网络任务调度问题, 提出一种基于最短曼哈顿距离的任务调度SMDS方案。该策略充分考虑核通信图中通信节点对之间最短曼哈顿路径,通过搜索算法寻找任务调度的目的节点,使用模拟退火算法确定任务调度对。实验结果显示,与传统的分布式任务调度 DTM策略相比,针对6*6、8*8和10*10的拓扑结构,SMDS实验方案在迁移次数方面的平均优化率分别为2208%、21.74%和23.02%。在平均跳数方面的平均优化率分别为24.04%、29.18%和23.04%,实现了系统温度优化。     

DFTS: A dynamic fault-tolerant scheduling for real-time tasks in multicore processors

This paper presents a dynamic scheduling for real-time tasks in multicore processors to tolerate single and multiple transient faults. The scheduling is performed based on three important issues: (1) current released tasks, (2) current available processor cores, and (3) consideration of the number of faults and their occurrences. Using tasks utilization along with a defined criticality threshold in the proposed scheduling method, current ready tasks are divided into critical- and noncritical ones. Based on whether a task is critical or noncritical, an appropriate fault-tolerance policy is exploited. Moreover, scheduling decisions are made to fulfill two key goals: (1) increasing scheduling feasibility and (2) decreasing the total tasks execution time. Several simulation experiments are carried out to compare the proposed method with two well-known methods, called checkpointing with rollback recovery and hardware replication. Experimental results reveal that in the presence of multiple transient faults, the feasibility rate of the proposed method is considerably higher than the other well-known fault-tolerance methods. Moreover, the average timing overhead of this method is lower than the traditional methods.     

用8031，DRAM和高速A/D实现快速数据采集

介绍了一个用８０３１，ＤＲＡＭ和高速Ａ／Ｄ等芯片构成的快速数据采集系统。该系统使Ａ／Ｄ转换的数据不经ＣＰＵ“中转”，而直接存入ＤＲＡＭ中。它具有硬件结构简单、价格低廉、易实现大容量存储等优点。本系统对模拟信号的采集并将采集数据送入存储器的周期为８μｓ。     

一种基于CICQ支持组播公平服务的调度策略*

针对目前基于CICQ(combined input and crosspoint queuing)支持组播的调度策略在公平性和实时性能保障方面存在的不足,提出了一种简单、高效的支持组播公平服务的分层平滑轮询调度算法——mFGSR (multicast fair service and group smoothed round robin)。mFGSR依据组播业务流的权重进行分组和平滑调度,具有良好的可扩展性和公平性能,能够适应实时业务的性能需求。理论分析和仿真结果表明,该算法具有良好的时延、吞吐量和公平性能。     

计算网格中动态负载平衡的分布调度模式

网格计算下对资源进行有效的管理和调度可以提高系统的利用率.在对现有若干调度方法的研究和分析基础上,针对计算网格中的负载平衡问题,提出了一种分布式网格作业调度模型,并给出相关算法.算法通过建立主从模式的负载信息收集机制,提供给节点全局负载信息,加速重负载节点的负载转移速度.通过有效的负载平衡模式,解决资源调度中负载平衡及其可靠性问题.     

Hadoop平台公平调度算法研究与优化

Hadoop Map Reduce框架的公平调度算法以统一的固定配置文件管理计算节点上计算槽的数量,这不能保障集群负载均衡,亦不能满足不同用户的资源需求。针对公平调度算法配置方式的不足,提出一种动态反馈的调度算法。该算法结合公平调度算法预先分配的特性,能够对计算节点上的计算槽进行动态调整。实验结果表明,基于动态反馈的改进算法有效地提高了集群的执行效率。     

Achieving fair service with a hybrid scheduling scheme for CICQ switches

Providing performance guarantees for arriving traffic flows has become an important measure for today’s routing and switching systems. However, none of current scheduling algorithms built on CICQ (combined input and cross-point buffered) switches can provide flow level performance guarantees. Aiming at meeting this requirement, the feasibility of implementing flow level scheduling is discussed thoroughly. Then, based on the discussion, it comes up with a hybrid and stratified fair scheduling (HSFS) scheme, which is hierarchical and hybrid, for CICQ switches. With HSFS, each input port and output port can schedule variable length packets independently with a complexity of O(1). Theoretical analysis show that HSFS can provide delay bound, service rate and fair performance guarantees without speedup. Finally, we implement HSFS in SPES (switch performance evaluation system) to verify the analytical results.     

支持公平服务的CICQ分层混合调度策略

为到达业务提供性能保障是衡量一个交换系统性能的重要参考.针对现有联合输入交叉点排队交换结构(CICQ)调度策略缺乏基于流的服务质量保障,探讨了在CICQ交换结构实施基于"流"调度的可能性,提出了一种能够为到达业务流的提供公平服务的分层混合调度策略(HSFS).HSFS采用分层的混合调度机制,每个输入、输出端口可独立地进行变长分组交换,其复杂度为O(1),具有良好可扩展特性.理论分析结果表明,HSFS无需加速便能为到达业务提供时延上限、速率和公平性保障.最后,基于SPES对HSFS的性能进行了评估.     

NoC关键问题

片上网络(NOC)作为复杂SoC通信的一种解决方案,受到了工业界和学术界的广泛重视.NoC设计涉及了从物理层到应用层诸多方面的问题,本文对NoC研究中的关键问题做简单的介绍.     

Non-preemptive scheduling to maximize the minimum global inter-completion time

Temporal load-balancing—“spreading out” the executions of tasks over time—is desirable in many applications. A form of temporal load-balancing is discussed, scheduling to maximize minimum minimum global inter-completion time (MGICT-scheduling). It is shown that MGICT-scheduling is, in general, NP-hard. A number of restricted classes of task systems are identified, which can be efficiently MGICT-scheduled. The technique is applied to a Defense Network System. Simulation results indicate that the proposed strategy achieves higher communication performance in multiprocessor systems. Specifically, our strategy significantly reduces average message delay and percentage of delayed messages.     

DPDS:一种处理资源调度算法

提出一种新颖的面向高级网络处理器(NP)的处理资源调度算法,称为基于复制的部分动态调度算法(Duplication-base Partial Dynamic Scheduling,DPDS),结合部分动态映射及任务复制策略,以改善NP的性能。DPDS从多个方面与已有算法不同,如处理单元是异构、全连通、多线程的,应用被分解为以持续数据包为输入的DAG任务,调度在初始化和运行时阶段均可调整。实验结果显示本算法比不具有动态复制阶段的算法在最大平均吞吐量上高出30%左右。