视频流调度策略的研究

视频流调度策略是视频点播系统中有效使用存储资源和网络资源的关键技术。该文研究了已有的多种流调度技术并分析了各种调度方法的优劣,在此基础上以补丁算法为基础提出了一种支持零延迟交互式操作的调度方法,并实验正明了这种方法在用户延迟、带宽消耗等方面的优越性。     

SANYO数码相机中被删除视频的恢复

MP4文件由一系列段组成,每个段的开头有1段长和段名,各占4字节,第1个段总是ftyp段,最重要的是mdat段,视频内容在此段,其数据关系在moov段,free段是空闲内容,用于填补数据簇。实验研究发现,SANYO数码相机拍摄MP4视频数据时的存储不连续,根据段分割为5个部分。根据MP4文件形成轨迹,结合MP4文件的结构可以恢复删除的视频文件。     

MHAL硬件抽象层数据流的分级调度设计

分析MHAL硬件抽象层的技术规范,针对MHAL硬件抽象层在数据调度方面的局限性,结合数据帧的优先级业务属性设计了具有实时数据传输保障的调度.按照优先级将数据帧进行队列管理,完成硬件抽象层数据流的分级调度.测试结果表明,该设计能够实现MHAL硬件抽象层数据流的分级调度,提高了MHAL硬件抽象层数据调度的灵活性,对推进SC...     

采用新代价模型的HMA网格资源调度

网格系统为管理和调度跨越不同区域的资源提供了一种虚拟框架。该文提出了一个基于HMA的网格资源调度系统以实现资源发现和调度;给出了一个新型的代价模型,它比传统的代价模型更多地考虑了资源发现代价和资源决策代价。随后,将新型代价模型集成到基于HMA的网格资源调度系统中。对比实验显示,新型代价模型下的最优解优于传统代价模型下的最优解。     

数据流操作符实时调度策略研究

处理无限的连续数据流的应用日益流行,数据流的质量意识越来越多得到人们的重视,数据流上的连续查询系统必须是自适应的,在系统可用资源无法满足需求的时候,需要对操作符进行有效的调度,将讨论DSMS操作符实时调度的各个方面,并提出一种适合时间序列QoS要求的查询处理任务调度策略,实验结果证明所采用的调度策略是有效的。     

Non-Clairvoyant Scheduling for Minimizing Mean Slowdown

We consider the problem of scheduling dynamically arriving jobs in a non-clairvoyant setting, that is, when the size of a job in remains unknown until the job finishes execution. Our focus is on minimizing the mean slowdown, where the slowdown (also known as stretch) of a job is defined as the ratio of the flow time to the size of the job. We use resource augmentation in terms of allowing a faster processor to the online algorithm to make up for its lack of knowledge of job sizes. Our main result is that the Shortest Elapsed Time First (SETF) algorithm, a close variant of which is used in the Windows NT and Unix operating system scheduling policies, is a $(1+\epsilon)$-speed, $O((1/\epsilon)^5 \log^2 B)$-competitive algorithm for minimizing mean slowdown non-clairvoyantly, when $B$ is the ratio between the largest and smallest job sizes. In a sense, this provides a theoretical justification of the effectiveness of an algorithm widely used in practice. On the other hand, we also show that any $O(1)$-speed algorithm, deterministic or randomized, is $\Omega(\min(n,\log B))$-competitive. The motivation for resource augmentation is supported by an $\Omega(\min(n,B))$ lower bound on the competitive ratio without any speedup. For the static case, i.e., when all jobs arrive at time 0, we show that SETF is $O(\log{B})$ competitive without any resource augmentation and also give a matching $\Omega(\log{B})$ lower bound on the competitiveness.     

一种成本和时间均衡的网格资源分类优化调度策略

针对时间和成本约束的网格资源调度问题,提出一种基于MinCTT算法的时间和成本均衡的网格资源分类优化调度算法.该算法综合考虑任务完成时间和执行成本两个QoS因素,由一个成本比值和时间比值的联合均衡值来综合衡量任务在资源上的完成时间和执行成本开销,根据任务估计平均价格,对资源进行分类调度.实验结果表明,该调度算法具有较好的调度性能,能有效的减少任务总的完成时间和执行成本,均衡因子的改变对该算法的调度性能影响较小,选择合适的均衡因子能实现优的调度.     

虚拟化数据中心全局能耗优化调度方法

虚拟化数据中心的制冷和供电设备能耗比重大且浪费严重,但当前虚拟化能耗优化的研究仅考虑IT设备能耗,针对该问题,通过对数据中心能耗逻辑的研究,提出一种虚拟化数据中心全局能耗优化调度方法。该方法通过感知数据中心负载和热分布状况,依据虚拟化调度规则生成动态调度策略,并对虚拟设备组的制冷供电设备进行同步调度,减少数据中心冗余制冷和设备空载损耗,以此最小化数据中心能耗。实验结果表明,该调度方法可节省制冷设备近26％的冗余制冷,并提升供电设备8％左右的供电效率,提高数据中心的能耗有效性,降低整体能耗。     

Algorithms for Minimizing Response Time in Broadcast Scheduling

In this paper we study the following problem. There are n pages which clients can request at any time. The arrival times of requests for pages are known in advance. Several requests for the same page may arrive at different times. There is a server that needs to compute a good broadcast schedule. Outputting a page satisfies all outstanding requests for the page. The goal is to minimize the average waiting time of a client. This problem has recently been shown to be NP-hard. For any fixed , 0 < \le &frac;, we give a 1/-speed, polynomial time algorithm with an approximation ratio of 1/(1 – ). For example, setting = &frac; gives a 2-speed, 2-approximation algorithm. In addition, we give a 4-speed, 1-approximation algorithm improving the previous bound of 6-speed, 1-approximation algorithm.     

Incentive Mechanisms for Resource Scaling-out Game of Stream Big Data Analytics

For stream big data analytics, a participated task always needs to scale out resources when its input data increases steeply. Typically, the resource scaling-out can be achieved by increasing the parallelism degree of the platform based on the experience. However, the resource scaling-out of each task produces additional cost not only from itself but also from other competitive tasks, which brings about great challenges to ensure the efficient utilization of resources. To solve it systematically, we consider the resource scaling-out as a non-cooperative game and formulate a total cost model including a risk function and a task execution time function. The total cost of resource scaling-out reflects the influence of topology structure for the benefit of a participated task. Then we introduce the concept of price of anarchy (POA) to this game and get its upper bounds under specific conditions to describe the efficiency loss of Nash equilibrium. Hence, two economic classic tax-based incentive policies: Pivotal Mechanism and Externality Mechanism are applied, to stimulate the participation of tasks. We make simulations in different scenarios including node degree and different characteristics of tasks. The simulations results show the influence of the topological structure and interdependent relationships of tasks for resource scaling-out game in the proposed scenarios and that the incentive mechanisms can effectively improve the performance of resource scaling-out.     

一种新型的视频码流识别算法

随着流媒体技术的兴起,越来越多的人选择从网上获得视频点播、网络电视、远程会议、远程教育等服务.但同时网络上充斥着一些淫秽、非法等有害视频,对社会造成很大危害.现有的基于视频内容的离线检测方法需要解码数据包,且匹配算法复杂度高,不适于数据量庞大的流媒体服务器或网关做实时检测.为此,提出一种基于媒体业务流特征的视频匹配算法,对流媒体服务器的码流进行实时检测和过滤.采用被广泛应用的MP4码流作为测试对象,分析了算法中各个参数对于判定结果的影响.实验结果表明,所提算法简单易行,无论是在拒真率还是取伪率方面都取得较为满意的结果.     

数据中心网络流量调度的研究进展与趋势

近年来,流量调度已经发展成为网络领域的热点研究问题.该问题主要决定何时以及以多大速率传输网络中的每条数据流,其对网络性能和应用性能都具有十分重要的影响.然而,在托管着许多大规模互联网应用的数据中心中,流量调度问题正面临着流量矩阵多变、流量种类混杂、以及流量突发等与流量模型相关的挑战.此外,随着数据中心规模的不断壮大,流量调度问题还面临着网络带宽动态化、网络拥塞随机化、以及网络目标多样化等与网络模型相关的挑战.为了进一步提升对数据中心流量调度的关注和理解,推动流调度技术在实际应用中的不断发展,本文分别从调度目标、调度方式和调度对象这三个维度对数据中心网络流调度的相关研究工作进行了分析和对比,并概括出如下结论:现有研究主要以分布式、集中式或混合式的调度方式对数据中心内、数据中心间或数据中心与用户间的流进行高效地调度,从而达到带宽保障、时限保障、最小化流完成时间、最小化Coflow完成时间、公平性保证、最小化流传输成本等目标.本文最后还指出了四个数据中心流调度的未来发展方向,并相应提出尚未解决的研究问题.     

Consistent Video Filtering for Camera Arrays

Visual formats have advanced beyond single‐view images and videos: 3D movies are commonplace, researchers have developed multi‐view navigation systems, and VR is helping to push light field cameras to mass market. However, editing tools for these media are still nascent, and even simple filtering operations like color correction or stylization are problematic: naively applying image filters per frame or per view rarely produces satisfying results due to time and space inconsistencies. Our method preserves and stabilizes filter effects while being agnostic to the inner working of the filter. It captures filter effects in the gradient domain, then uses input frame gradients as a reference to impose temporal and spatial consistency. Our least‐squares formulation adds minimal overhead compared to naive data processing. Further, when filter cost is high, we introduce a filter transfer strategy that reduces the number of per‐frame filtering computations by an order of magnitude, with only a small reduction in visual quality. We demonstrate our algorithm on several camera array formats including stereo videos, light fields, and wide baselines.     

Minimizing Makespan in Batch Machine Scheduling

We study the scheduling of a set of n jobs, each characterized by a release (arrival) time and a processing time, for a batch processing machine capable of running at most B jobs at a time. We obtain an O(n log n)-time algorithm when B is unbounded. When there are only m distinct release times and the inputs are integers, we obtain an O(n(BR_max)^m-1(2/m)^m-3)-time algorithm where R_max is the difference between the maximum and minimum release times. When there are k distinct processing times and m release times, we obtain an O(n log m + k^k+2 B^k+1 m² log m)-time algorithm. We obtain even better algorithms for m=2 and for k=1. These algorithms improve most of the corresponding previous algorithms for the respective special cases and lead to improved approximation schemes for the general problem.     

视像中的摄像机运动检测

摄像机的运动信息是视像内容检索中的一种重要特征。文中介绍了两种基于全局运动的摄像机运动检测方案。首先提取视像中的运动特征作为原始数据,然后分别使用了迭代最小二乘法和支持向量机分类的方法进行摄像机运动的检测,通过对试验结果的对比,前一种方案可更有效地完成摄像机运动类型的判断。     

视像中的摄像机运动检测

摄像机的运动信息是视像内容检索中的一种重要特征。文中介绍了两种基于全局运动的摄像机运动检测方案。首先提取视像中的运动特征作为原始数据，然后分别使用了迭代最小二乘法和支持向量机分类的方法进行摄像机运动的检测，通过对试验结果的对比，前一种方案可更有效地完成摄像机运动类型的判断。     

A Cost-Based Approach to Adaptive Resource Management in Data Stream Systems

Data stream management systems need to adaptively control their resources, since stream characteristics and query workload may vary over time. In this paper, we investigate an approach to adaptive resource management for continuous sliding-window queries that adjusts window sizes and time granularities to keep resource usage within bounds. These two novel techniques differ from standard load shedding approaches based on sampling, as they ensure exact query answers for given user-defined quality of service specifications, even under query reoptimization. In order to quantify the effects of both techniques on the various operations in a query plan, we develop an appropriate cost model for estimating operator resource allocation in terms of memory usage and processing costs. A thorough experimental study not only validates the accuracy of our cost model but also demonstrates the efficacy and scalability of the proposed techniques.     

基于Hi3531的ONVIF高清网络摄像机视频数据接入设计

基于海思半导体的嵌入式32位视频处理器Hi3531,提出了接入兼容ONVIF规范的高清网络摄像机视频数据的方法,描述了兼容ONVIF规范的客户端和服务器端的握手过程,介绍了H.264视频流的RTSP数据包的结构和解RTSP数据包的流程和实例.该设计被用于LED/LCD多屏拼接设备的基于IP的视频数据的接入,取得了很好的效果.     

云数据中心基于负载权重的负载均衡调度算法

针对现有云数据中心的多维资源利用不均衡问题,提出基于资源负载权重的动态多资源负载均衡调度算法。算法结合服务器各维度资源动态负载情况,构造层次分析法（AHP）判断矩阵来处理多维资源对于负载均衡影响权重大小,在此基础上综合考虑任务资源需求,将任务放置到合适服务器来改善资源利用,实现资源间负载均衡。平台仿真显示新算法可有效提高利用率低的资源的利用效率,在提高整体资源利用率、降低资源间负载不均衡率方面有优势。