基于QoS的磁盘调度策略

随着视频点播、视频会议、视频监控、数字图书馆等流媒体应用的普及，流媒体服务器存储资源管理成为制约服务质量的瓶颈之一。根据多媒体服务器的性能要求，提出了一种支持QoS的磁盘调度策略。它由三个主要部分组成：探测模块、负载监测模块和自适应管理模块。探测模块，负责判断当前的资源情况能否满足服务请求；自适应模块，根据负载监删模块检测到的负载变化情况，动态调整服务周期在实时请求和尽力服务请求之间的分配。实验表明此磁盘调度策略能在保证实时请求无抖动执行的同时，明显减少了非实时请求的响应时间。     

双头镜橡磁盘的实时调度算法及性能评价

本文对双头镜像磁盘系统模型进行实时扩展,并提出了三种实时调度算法：最早截止期优先算法（ＥＤＦ）,可满足的最早截止期优先算法（Ｆ－ＥＤＦ）和忽视超时限请求算法（ＩＧＭ－ＥＤＦ）。这三种算法充分考虑了Ｉ／Ｏ请求的截止期限,使双头镜像磁盘系统能更好地满足实时需求,在进行了性能模拟后,发现实时调度算法比非实时算法能更好地满足时Ｉ／Ｏ请求的时限要求。三种实时调度算法中,适用于硬实时应用的ＩＧＭ－ＥＤＦ的性能     

双头镜像磁盘的实时调度算法及性能评价

本文对双头镜像磁盘系统模型进行实时扩展,并提出了三种实时调度算法：最早截止期优先算法（ＥＤＦ）,可满足的最早截止期优先算法（Ｆ－ＥＤＦ）和忽视超时限请求算法（ＩＧＭ－ＥＤＦ）．这三种算法充分考虑了Ｉ／Ｏ请求的截止期限,使双头镜像磁盘系统能更好地满足实时需求．在进行了性能模拟后,发现实时调度算法比非实时算法能更好地满足实时Ｉ／Ｏ请求的时限要求．三种实时调度算法中,适用于硬实时应用的ＩＧＭ－ＥＤＦ的性能最好,Ｆ－ＥＤＦ算法的性能次之,它适用于软实时环境．     

一种面向Web服务的分级服务模型*

以服务响应时间为QoS参数,提出了一种面向Web服务的分级QoS方法,该方法从预测请求响应时间入手,通过区分操作类型并采用优先级队列调度策略,进而保证请求响应时间.在ONCE平台内置SOAP引擎SOAPExpress的基础上进行了原型实现.实验表明,该方法能有效地保证不同级别用户的请求响应时间,实现服务分级.     

非固定双头镜像磁盘实时调度算法的研究

文章给出一个实时非固定双头镜像磁盘系统的形式化模型.该磁盘模型中的每个双头磁盘都有两个相互独立的磁臂,能够独立地完成寻找磁道过程.针对该磁盘系统,文章研究了3种实时调度算法.模拟实验表明,“忽略超截止期调度算法”的性能最好,因为它忽略了对超截止期限实时请求的处理.文章同时分析了固定双头镜像磁盘与非固定双头镜像磁盘之间的性能差别.实验结果表明,由于非固定双头磁盘的两个磁头可以独立寻找磁道,因此非固定双头镜像磁盘的性能比固定双头镜像磁盘的性能要好.     

基于混合业务QoS的LTE跨层调度算法

在众多资源分配的调度算法中,区别实现混合业务QoS要求的调度策略研究不多。针对现有调度算法不能同时满足多用户实时和非实时业务性能需求,提出了一种保证混合业务QoS的LTE系统下行资源分配算法。新算法采用跨层设计思想下的资源块分配机制,在EXP算法的基础上引入权重因子。仿真表明新算法能够大幅度降低LTE系统用户丢包率,改善用户公平性和吞吐量性能。     

一种基于请求大小的固态盘I／O调度算法

对于同类型的I／O请求,基于闪存固态盘的请求响应时间与请求大小基本呈线性比例关系,并且固态盘的读写性能具有非对称性。针对该特性,提出一种基于请求大小的固态盘I／O调度（SIOS）算法,从I／O请求平均响应时间的角度提高固态盘设备的I／O性能。根据读写性能的非对称性,对读写请求进行分组并且优先处理读请求。在此基础上首先处理等待队列中的小请求,从而减少队列中请求的平均等待时间。采用SLC和MLC2种类型的固态盘进行实验,在5种测试负载的驱动下与Linux系统中的3种调度算法进行比较,对于SLC固态盘,SIOS平均响应时间分别减少18．4％、25．8％、14．9％、14．5％和13．1％,而对于MLC固态盘,平均响应时间分别减少16．9％、24．4％、13．1％、13．0％和13．7％,结果表明,SIOS能有效减少I／O请求的平均响应时间,提高固态盘存储系统的I／O性能。     

一种海量存储系统二级缓存的设计与实现

引入新颖固态存储技术和DRAM与固态硬盘（SSD）混合的缓存架构，提出一种海量存储系统的二级缓存策略，通过回写策略能够有效减少SSD缓存的小写问题，并对两级缓存架构下建立的逻辑磁盘进行测试，结果表明在请求平均响应时间上取得了优化。     

Web集群服务器的分离式调度策略

主要用排队论方法讨论了Web集群整体性能与请求调度策略之间的关系，所获得的结论是：在Web集群非过载情况下，一部分后端服务器仅处理静态请求而另一部分后端服务器仅处理动态请求的分离式调度策略要好于所有后端服务器既处理静态请求又处理动态请求的混合式调度策略。用SPECweb99测试工具所做的实际测试更进一步证明：当负载参数为120个连接时，采用分离式调度策略的Web集群服务器可完成63个连接，而采用混合式调度策略的Web集群服务器仅能完成36个连接，性能提高了22.5%。     

一种新颖的带模糊截止时限的磁盘调度算法

设计了一种新的基于截止时限的磁盘调度算法，该算法支持带多优先级的请求。对于某些实时要求，其截止时限是不确定的或者不精确的，该算法采用模糊集来描述这类不确定性，模糊截止时限的隶属度函数表示对请求完成时间的满意程度。调度的目的是最优的指定优先级，使得截止时限的满意程度最大化。根据请求截止时限的不同，把满意程度划分为若干连续的区间。在每个不同的区间内，每个请求都对应有修正的截止时限，把请求按照其修正的截止时限非减的顺序分配优先级，才能实现请求优先级的最优配置。仿真结果表明该算法能有效的分配请求的优先级，降低请求的丢失率，保证了更多的请求得到满足。     

I/O issues in a multimedia system

In future computer system design, I/O systems will have to support continuous media such as video and audio, whose system demands are different from those of data such as text. Multimedia computing requires us to focus on designing I/O systems that can handle real-time demands. Video- and audio-stream playback and teleconferencing are real-time applications with different I/O demands. We primarily consider playback applications which require guaranteed real-time I/O throughput. In a multimedia server, different service phases of a real-time request are disk, small computer systems interface (SCSI) bus, and processor scheduling. Additional service might be needed if the request must be satisfied across a local area network. We restrict ourselves to the support provided at the server, with special emphasis on two service phases: disk scheduling and SCSI bus contention. When requests have to be satisfied within deadlines, traditional real-time systems use scheduling algorithms such as earliest deadline first (EDF) and least slack time first. However, EDF makes the assumption that disks are preemptable, and the seek-time overheads of its strict real-time scheduling result in poor disk utilization. We can provide the constant data rate necessary for real-time requests in various ways that require trade-offs. We analyze how trade-offs that involve buffer space affect the performance of scheduling policies. We also show that deferred deadlines, which increase buffer requirements, improve system performance significantly     

A new real time disk-scheduling method based on GSR algorithm

Disk scheduling has an important role in QOS guarantee of soft real-time environments such as video-on-demand and multimedia servers. Since now, some disk-scheduling algorithms have been proposed to schedule real-time disk requests. One of the most recent algorithms is global seek-optimizing real-time (GSR) that schedules the disk requests with different ready times by a global regrouping scheme. In the present paper, we propose a real-time disk-scheduling algorithm based on GSR that is called IGSR (improved GSR). IGSR creates the scan-groups of the requests and tries to find a good feasible schedule by optimized grouping with considering another chance for tasks that miss their deadlines at initial grouping. With regard to the admission policy of tasks, two different version of proposed method are presented: the first one has been designed for the case that all the disk requests available simultaneously and second one has been designed for the case that requests are admitted dynamically (GSR does not support the second one). It means that in the second case, the request queue may change when a task is running but in the first one it does not change. Simulation results showed IGSR outperformed GSR and some other related works in terms of maximum supportable streams, number of missed deadlines, and disk throughput.     

Operating system support for a video-on-demand file service

This paper describes the design and implementation of a continuous media file server intended for use in emerging video-on-demand applications. The main focus and contribution of the paper is in scheduling and admission-control algorithms for accessing the server's processor and storage resources. The scheduling algorithms support multiple classes of tasks with diverse performance requirements and allow for the co-existence of guaranteed real-time requests with sporadic, and unsolicited requests. The scheduler maintains performance guarantees for real-time streams in the presence of unpredictably varying non-real-time traffic while ensuring system stability even during overloads. A prototype video file server was implemented on an Intel 486 platform. Performance results show that a large number of streams can be supported, while maintaining efficient utilization of system resources.     

A buffer-inventory-based dynamic scheduling algorithm for multimedia-on-demand servers

We present a producer-consumer model of multimedia-on-demand (MOD) servers. The producer retrieves media data from a disk and places it into a set of buffers, while the consumer sends out the data in the buffers to the users. We develop for the producer a buffer-inventory-based dynamic scheduling (BIDS) algorithm that guarantees non-zero inventory and non-overflow of data in the buffers to meet the continuity requirement and no-loss of data for each media stream. The algorithm can deal with heterogeneous me dia streams as well as the transient circumstances upon service completions and arrivals of new requests. To smooth out the impact of bursty data of variable-bit-rate media streams and therefore increase the maximum admissible load of requests, we also introduce into the scheduling scheme a time-scale-dependent peak consumption rate and a virtual cycle time. Based on BIDS, an effective admission control mechanism can be easily established by checking two simple conditions respectively on the overall system load and buffer size. Our algorithm is very easy to implement. Experiments carried out with an actual disk system and real video stream data verify that it is more robust compared to static scheduling algorithms previously proposed in the literature, especially when handling variable-bit-rate media streams.     

A genetic based disk scheduling method to decrease makespan and missed tasks

Disk scheduling is an operating system process to service disk requests. It has an important role in QOS guarantee of soft real-time environments such as video-on-demand and multimedia servers. Since now, some disk scheduling algorithms have been proposed to schedule disk requests in an optimized manner. Most of these methods try to minimize makespan by decreasing the number of disk head seeks as one of the slowest operations in modern computers and crucial for system performance because it usually takes some milli-seconds. In this paper, we propose a new disk scheduling method based on genetic algorithm that considers makespan and number of missed tasks simultaneously. In the proposed method, a new coding scheme is presented which employs simple GA procedures such as crossover and mutation and a penalty function in fitness. To get the best performance of the proposed method, its parameters such as number of chromosomes in initial population, mutation, and crossover probabilities, etc have been adjusted by applying it on some sample problems. The algorithm has been tested on several problems and its results were compared with well-known related methods. Experimental results showed that the proposed method worked very well and excelled most related works in terms of miss ratio and average seeks.     

APEX: adaptive disk scheduling framework with QoS support

APEX is an adaptive disk scheduling framework with Quality-of-Service (QoS) support designed for environments with highly varying disk bandwidth usage. APEX is based on a three-layer scheduling architecture: (1) the upper layer realizes different service classes using a set of queues; (2) the mid-layer distributes available disk bandwidth among these queues; and (3) the lower layer is handled by the disk itself, which does the final ordering of disk requests. We demonstrate the use of APEX in an example scenario, a Learning-on-Demand (LoD) application supported by a multimedia system, where students can search for and playback multimedia-based learning material. In this paper, we present the scheduling concepts of APEX which are based on an extended token bucket algorithm. The disk requests scheduled for service are assembled into batches in order to exploit the intelligence of modern disks. Combined with a specialized work-conservation scheme, this enables APEX to apply bandwidth where it is needed, without the loss of efficiency. We demonstrate, through simulations, that APEX provides both higher throughput and lower response times than other mixed-media disk schedulers while still avoiding deadline violations for real-time requests. We also show its robustness with respect to misaligned bandwidth allocation. The work was conducted while Ketil Lund was an employee at UniK – University Graduate Center, Kjeller, Norway.     

一个实时与尽力服务并存的队列调度方案

某些工业环境往往有一个或多个用于监测和/或控制的周期性实时系统,而今,这样的环境也难以抵御Internet的吸引和渗透。如果在单个系统中,既能保证实时数据的正常传递,又能与Internet连通实现尽力服务,应该是一个值得研究的课题。为此提出了IaI（Industry and Internet）交换设备的概念,主要讨论了其中的队列调度一环。以三个实时队列和一个尽力服务队列为前提,分析了四种队列模型,给出了实时数据包最长等待时间的计算公式。     

Disk scheduling in video editing systems

Modern video servers support both video-on-demand and nonlinear editing applications. Video-on-demand servers enable the user to view video clips or movies from a video database, while nonlinear editing systems enable the user to manipulate the content of the video database. Applications such as video and news editing systems require that the underlying storage server be able to concurrently record live broadcast information, modify prerecorded data, and broadcast an authored presentation. A multimedia storage server that efficiently supports such a diverse group of activities constitutes the focus of this study. A novel real-time disk scheduling algorithm is presented that treats both read and write requests in a homogeneous manner in order to ensure that their deadlines are met. Due to real-time demands of movie viewing, read requests have to be fulfilled within certain deadlines; otherwise, they are considered lost. Since the data to be written into disk is stored in main memory buffers, write requests can be postponed until critical read requests are processed. However, write requests still have to be processed within reasonable delays and without the possibility of indefinite postponement. This is due to the physical constraint of the limited size of the main memory write buffers. The new algorithm schedules both read and write requests appropriately, to minimize the amount of disk reads that do not meet their presentation deadlines, and to avoid indefinite postponement and large buffer sizes in the case of disk writes. Simulation results demonstrate that the proposed algorithm offers low violations of read deadlines, reduces waiting time for lower priority disk requests, and improves the throughput of the storage server by enhancing the utilization of available disk bandwidth