Integrating Priority with Share in the Priority-Based Weighted Fair Queuing Scheduler for Real-Time Networks

The Weighted Fair Queuing (WFQ) scheduler has been closely studied due to its desirable properties of bandwidth guarantee and bounded delay. However, the queuing delay bound of a communication session is tightly coupled with the session's allocated service share. To receive a low queuing delay, a session must reserve a high share. In this paper, we study a new fair queuing algorithm called Priority-based Weighted Fair Queuing (PWFQ). PWFQ combines a session's allocated share to achieve the bandwidth guarantee and the session's priority to adjust the delay bound inside a sliding window. The new algorithm decouples the delay from the service share so that a session with a low share but a high priority may still receive a small delay. We analyze the worst-case delay bound of PWFQ and propose a simple algorithm to assign session priorities.     

保证无线上行链路TCP公平的调度算法

针对无线局域网中上行链路TCP流之间存在严重的无线信道资源分配不公平问题,提出一种上行链路TCP流的调度算法UFWFQ。该算法在接入节点上对上行TCP流采用与WFQ算法相同的轮询机制,根据流的传送速率动态计算其服务概率,分配给高速发送流较大的权重,使各上行TCP流占用的信道时间相等,以保证各流的加权公平性,提高网络的总吞吐率。仿真实验结果验证了该算法的有效性。     

Partition oriented frame based fair scheduler

Proportionate fair schedulers provide an effective methodology for scheduling recurrent real-time tasks on multiprocessors. However, a drawback in these schedulers is that they ignore a task’s affinity towards the processor where it was executed last, causing frequent inter-processor task migrations which ultimately results in increased execution times. This paper presents Partition Oriented Frame Based Fair Scheduler (POFBFS), an efficient proportional fair scheduler for periodic firm and soft real-time tasks that ensures a bounded number of task migrations. Experimental results reveal that POFBFS can achieve 3 to 100 times reduction in the number of migrations suffered with respect to the General-ERfair algorithm (for a set of 25 to 100 tasks running on 2 to 8 processors) while simultaneously maintaining high fairness accuracy.     

TCP／IP拥塞控制研究

综述了Internet上TCP／IP拥塞控制研究方面一些最新的工作,分析了拥塞控制的原理、TCP／IP拥塞控制所使用的典型技术,并着重论述了TCP／IP拥塞控制所面临的问题,这包括自相似性问题、效率问题、公平性问题、算法改进、区分服务和多点广播中拥塞控制和TCP／IP在特殊网络（ATM网和卫星网）上拥塞控制等问题,并提出了其进一步的研究方向。     

A metric of fairness for parallel job schedulers

Fairness is an important aspect in queuing systems. Several fairness measures have been proposed in queuing systems in general and parallel job scheduling in particular. Generally, a scheduler is considered unfair if some jobs are discriminated whereas others are favored. Some of the metrics used to measure fairness for parallel job schedulers can imply unfairness where there is no discrimination (and vice versa). This makes them inappropriate. In this paper, we show how the existing approach misrepresents fairness in practice. We then propose a new approach for measuring fairness for parallel job schedulers. Our approach is based on two principles: (i) as jobs have different resource requirements and find different queue/system states, they need not have the same performance for the scheduler to be fair and (ii) to compare two schedulers for fairness, we make comparisons of how the schedulers favor/discriminate individual jobs. We use performance and discrimination trends to validate our approach. We observe that our approach can deduce discrimination more accurately. This is true even in cases where the most discriminated jobs are not the worst performing jobs. Copyright © 2008 John Wiley & Sons, Ltd.     

Embedded fuzzy expert system for Adaptive Weighted Fair Queueing

This paper introduces an embedded fuzzy expert system for Adaptive Weighted Fair Queueing (AWFQ) located in the network traffic router to update weights for output queues. WFQ algorithm allows differentiated service for traffic classes according to Quality of Service (QoS) requirements. Link sharing and packet scheduling methods are the most critical factors when guaranteeing QoS. There are many different scheduling mechanisms but adequate and adaptive QoS aware scheduling solutions are still in a phase of development due to the rapid growth of multimedia in the Internet. The proposed AWFQ model in this work simplifies the link sharing to two service classes: one for UDP and another for TCP. The implementation of the model is based on adaptive change of weight coefficients that determine the amount of allowed bandwidth for the service class. New weight coefficients are calculated periodically on routers according to developed embedded fuzzy expert system. It is shown through simulations that the AWFQ model is more stable and reacts faster to different traffic states than the traditional WFQ scheduler. The embedded expert system adjusts the weights of AWFQ with two parameters that are based on the share of the UDP and TCP input traffic data rate and the change of the share of the UDP and TCP input data rate.     

基于层次化的网格资源三层调度模型

在分析现有的资源调度方案及模型的基础上,提出了基于层次化的网格资源三层调度模型．它由主调度器、次级调度器和计算节点组成。主调度器根据任务的性质和需求,并参考下层次级调度器的执行情况,将部分任务分发到各次级调度器上,实现了主调度器与次级调度器之间的并行工作。基于该模型提出轮循任务分发策略。通过分析和模拟．该资源调度模型及任务分发策略在调度性能上明显优于集中式调度方案。     

Hardware design and implementation of packet fair queuing algorithms for the quality of service support in the high-speed internet

The increasing amount of real-time traffic carried over the Internet requires end-to-end quality of service (QoS) support. To this end, the QoS Schedulers, that are implemented in routers, assign the available bandwidth resources to packet flows according to their respective allocated rates. Packet Fair Queuing (PFQ) schedulers can provide fair service and low end-to-end delay bound to the traffic flows. However, they have higher implementation complexity compared to other algorithms, because of the requirements of tracking the system state, and searching for the packet to get service among all flows, that are queued at the outgoing interface. QoS scheduling is a data plane functionality, which requires hardware implementation for high speed router interfaces. The previous works on hardware implementation of PFQ schedulers are specific to certain algorithms, and they do not provide any results on real hardware platforms. In this paper, we present a general hardware design framework for PFQ schedulers, and apply this framework to the WF²Q+ PFQ algorithm to demonstrate its properties. We carry out the entire implementation of the WF²Q+ algorithm on an FPGA, and evaluate its performance with real traffic flows. In addition, we implement WFQ as a second PFQ algorithm to demonstrate the generality of the framework.     

Profit data caching and hybrid disk‐aware Completely Fair Queuing scheduling algorithms for hybrid disks

Recently, a hybrid disk drive that integrates a small amount of flash memory within a mechanical drive has received significant attention. The hybrid drive extends the storage hierarchy by using flash memory to cache data from the mechanical disk. Unfortunately, current caching architectures fail to fully exploit the potential of the hybrid drive. Furthermore, current disk input/output (I/O) schedulers are optimized for rotational mechanical disk drives and thus must be re‐targeted for the hybrid disk drive. In this paper, we propose a new data caching scheme, called Profit Caching, for hybrid drives. Profit Caching is a self‐optimizing caching algorithm. It considers and seamlessly integrates all possible data characteristics that impact the performance of hybrid drives, including read count, write count, sequentiality, randomness, and recency, to determine the caching policy. Moreover, we propose a hybrid disk‐aware Completely Fair Queuing (HA‐CFQ) scheduler to avoid unnecessary I/O anticipations of the CFQ scheduler. We have implemented Profit Caching and HA‐CFQ scheduler in the Linux kernel. Coupled with a trace‐driven simulator, we have also conducted detailed experiments under a variety of workloads. Experimental results show that Profit Caching provides significantly improved performance compared with the previous schemes. In particular, the throughput of Profit Caching outperforms previous Random Access First and FlashCache caching schemes by factors of up to 1.8 and 7.6, respectively. In addition, the HA‐CFQ scheduler reduces the total execution time of the CFQ scheduler by up to 1.74%. Finally, the experimental results show that the runtime overhead of Profit Caching is extremely insignificant and can be ignored. Copyright © 2014 John Wiley & Sons, Ltd.     

大规模短时间任务的低延迟集群调度框架

大规模数据分析环境中,经常存在一些持续时间较短、并行度较大的任务。如何调度这些低延迟要求的并发作业是目前研究的一个热点。现有的一些集群资源管理框架中,集中式调度器由于主节点的瓶颈无法达到低延迟的要求,而一些分布式调度器虽然达成了低延迟的任务调度,但在最优资源分配以及资源分配冲突方面存在一定的不足。从大规模实时作业的需求出发,设计和实现了一个分布式的集群资源调度框架,以满足大规模数据处理的低延迟要求。首先提出了两阶段调度框架以及优化后的两阶段多路调度框架;然后针对两阶段多路调度过程中存在的一些资源冲突问题,提出了基于负载平衡的任务转移机制,从而解决了各个计算节点的负载不平衡问题;最后使用实际负载以及一个模拟调度器对大规模集群中的任务调度框架进行了模拟和验证。对于实际负载,所提框架的调度延迟控制在理想调度的12%以内;在模拟环境下,该框架与集中式调度器相比在短时间任务的延迟上能够减少40%以上。     

Fair allocation of utilities in multirate multicast networks: aframework for unifying diverse fairness objectives

We study fairness in a multicast network. We assume that different receivers of the same session can receive information at different rates. We study a fair allocation of utilities, where the utility of a bandwidth is an arbitrary function of the bandwidth. The utility function is not strictly increasing, nor continuous in general. We discuss fairness issues in this general context. Fair allocation of utilities can be modeled as a nonlinear optimization problem. However, nonlinear optimization techniques do not terminate in a finite number of iterations in general. We present an algorithm for computing a fair utility allocation. Using specific fairness properties, we show that this algorithm attains global convergence and yields a fair allocation in polynomial number of iterations     

命名数据网络中的一种主动拥塞控制策略

为解决命名数据网络（Named Data Networking,NDN）中的拥塞控制问题,在加权公平排队（Weighted Fair Queuing,WFQ）算法的基础上,提出了基于即时调整兴趣包发送速率的名字加权公平排队（Name Weighted Fair Queuing,NWFQ）算法。当网络拥塞时,利用基于令牌桶算法的速率限制机制对超速流进行降速惩罚,同时更新兴趣包中的拥塞信息域并将其逐跳反馈给下游路由器;利用数据包将拥塞信息反馈给请求端,请求端据此调整兴趣包的发送速率,从而解决网络拥塞。基于ndnSIM的仿真结果表明,该算法能有效提升瓶颈链路利用率并接近95%,同时保证较低的丢包率和平均流完成时间。     

Computing planar swept polygons under translation

A translational sweep is the translating of a polygon, called the generatrix G, around another polygon, called the directrix D, under two conditions: (1) G is always in contact with D; and (2) the interiors of G and D do not intersect. Three classes of translational sweep are studied, including the case in which both G and D are convex; the case in which G is convex, D monotone; and the case in which both are monotone. Efficient algorithms for computing the trajectory and the swept area as well as geometric and computational properties are presented for each class. A notion called the inverse generatrix, which reveals a duality between the trajectory and the swept polygon, is introduced to reduce complexity.     

Achieving service rate objectives with decay usage scheduling

Decay usage scheduling is a priority- and usage-based approach to CPU allocation in which preference is given to processes that have consumed little CPU in the recent past. The author develops an analytic model for decay usage schedulers running compute-bound workloads, such as those found in many engineering and scientific environments; the model is validated from measurements of a Unix system. This model is used in two ways. First, ways to parameterize decay usage schedulers are studied to achieve a wide range of service rates. Doing so requires a fine granularity of control and a large range of control. The results show that, for a fixed representation of process priorities a larger range of control makes the granularity of control coarser, and a finer granularity of control decreases the range of control. A second use of the analytic model is to construct a low overhead algorithms for achieving service rate objectives. Existing approaches require adding a feedback loop to the scheduler. This overhead is avoided by exploiting the feedback already present in decay usage schedulers. Using both empirical and analytical techniques, it is shown that the algorithm is effective and that it provides fairness when the system is over- or under-loaded     

面向网络能效优化的动态权重队列管理算法

针对流量传输过程中能效优化的问题,提出一种面向网络能效优化的动态权重队列管理算法DW_WFQ。该算法在加权公平队列(WFQ)的基础上通过动态地分配各类业务流的权重,以更加灵活的方式分配各类业务流的服务速率,进而与连续流速度缩放模型的能效函数相结合,推导出了该调度算法的能耗模型并且对其进行了能效优化。通过Matlab仿真,进行了DW_WFQ、先到先服务(FCFS)和WFQ三种算法的能耗对比,仿真结果表明:所提的流量调度算法在满足业务流服务质量(QoS)约束的基础上,能够有效降低系统能耗。     

Enhanced cluster computing performance through proportional fairness

The performance of cluster computing depends on how concurrent jobs share multiple data center resource types such as CPU, RAM and disk storage. Recent research has discussed efficiency and fairness requirements and identified a number of desirable scheduling objectives including so-called dominant resource fairness (DRF). We argue here that proportional fairness (PF), long recognized as a desirable objective in sharing network bandwidth between ongoing data transfers, is preferable to DRF. The superiority of PF is manifest under the realistic modeling assumption that the population of jobs in progress is a stochastic process. In random traffic the strategy-proof property of DRF proves unimportant while PF is shown by analysis and simulation to offer a significantly better efficiency–fairness tradeoff.     

队列调度算法在网络中的应用研究

作为保证QoS的一种重要手段,队列调度算法近年来引起了网络研究者的广泛关注。本文首先介绍了队列调度问题及一些常用的队列调度算法,然后提出一个非GPS模型的队列模型及调度算法——WDQ算法(Weighted Delay Queuing,基于权重的延迟队列),并且解释了这种算法能够有效抵抗通信量的突发,具有控制不同权重分组延迟的能力,对于提高和改善网络服务质量QoS方面的研究和网络运行情况的研究具有积极意义。     

Supervisory control for real-time scheduling of periodic and sporadic tasks with resource constraints

In the framework of supervisory control of timed discrete event systems, this paper addresses the design problem of a real-time scheduler that meets stringent time constraints of periodic tasks and sporadic tasks which exclusively access shared resources. For this purpose, we present the timed discrete event models of execution of periodic tasks and sporadic tasks and resource access for shared resources. Based on these models, we present the notion of deadlock-free and schedulable languages that contain only deadline-meeting sequences which do not reach deadlock states. In addition, we present the method of systematically computing the largest deadlock-free and schedulable language, and it is also shown that schedulability analysis can be done using this language. We further show that the real-time scheduler achieving the largest deadlock-free and schedulable language is optimal in the sense that there are no other schedulers to achieve schedulable cases more than those achieved by the optimal scheduler.     

Libra: a computational economy‐based job scheduling system for clusters

Clusters of computers have emerged as mainstream parallel and distributed platforms for high‐performance, high‐throughput and high‐availability computing. To enable effective resource management on clusters, numerous cluster management systems and schedulers have been designed. However, their focus has essentially been on maximizing CPU performance, but not on improving the value of utility delivered to the user and quality of services. This paper presents a new computational economy driven scheduling system called Libra, which has been designed to support allocation of resources based on the users' quality of service requirements. It is intended to work as an add‐on to the existing queuing and resource management system. The first version has been implemented as a plugin scheduler to the Portable Batch System. The scheduler offers market‐based economy driven service for managing batch jobs on clusters by scheduling CPU time according to user‐perceived value (utility), determined by their budget and deadline rather than system performance considerations. The Libra scheduler has been simulated using the GridSim toolkit to carry out a detailed performance analysis. Results show that the deadline and budget based proportional resource allocation strategy improves the utility of the system and user satisfaction as compared with system‐centric scheduling strategies. Copyright © 2004 John Wiley & Sons, Ltd.     

PRED:一种配合队列调度的RED算法

论文讨论了队列管理和队列调度的关系,提出了一种新的基于势的RED机制:PRED,以增强SPFQ调度机制的公平性,来达到整个报文处理系统的性能改善。通过严格的仿真验证,同其他的队列管理机制相比,PRED同SPFQ的结合能够最大限度地利用系统资源,提高服务的公平性。