Scalable multimedia disk scheduling

Mokbel, Mohamed F.; Aref, Walid G.; Elbassioni, Khaled; Kamel, Ibrahim

doi:10.1109/icde.2004.1320022

Cited by 12 publications

(10 citation statements)

References 23 publications

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“…In particular, space-filling curves have been used as a mapping scheme that supports spatial join algorithms (Bohm et al 1999;Orenstein 1986), spatial access methods (Faloutsos and Rong 1991;Kamel and Faloutsos 1994;Lawder and King 2001), efficient processing of range queries (Asano et al 1997;Faloutsos 1988;Jagadish 1990), nearest-neighbor queries (Liao et al 2001), data-parallel applications (Ou et al 1995), disk scheduling (Mokbel et al 2004), memory management (Mellor-Crummey et al 1999), mesh-indexing (Niedermeier et al 1997) and image processing (Zhang and Webber 1993).…”

Section: Historical Backgroundmentioning

confidence: 99%

“…Scheduler parameters can be mapped to space dimensions and an SFC-based scheduler is used. The reader is referred to Mokbel et al (2004) to gain more insight regarding the applicability of irregularity in multi-media disk schedulers.…”

Section: Multimedia Disk Schedulingmentioning

confidence: 99%

“…Consider the problem of disk scheduling in multimedia servers (Mokbel et al 2004). In addition to maximizing the bandwidth of the disk, the scheduler has to take into consideration the realtime constraints of the page requests, e.g., as in the case of video streaming.…”

Section: Multimedia Disk Schedulingmentioning

confidence: 99%

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Space-Filling Curves

Kang¹

2016

Encyclopedia of GIS

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A space-filling curve (SFC) is a way of mapping a multi-dimensional space into a one-dimensional space. It acts like a thread that passes through every cell element (or pixel) in the multidimensional space so that every cell is visited exactly once. Thus, a space-filling curve imposes a linear order of points in the multi-dimensional space. A D-dimensional space-filling curve in a space of N cells (pixels) of each dimension consists of N D 1 segments where each segment connects two consecutive D-dimensional points. There are numerous kinds of space-filling curves (e.g., Hilbert, Peano, and Gray). The difference between such curves is in their way of mapping to the one-dimensional space, i.e., the order that a certain space-filling curve traverses the multi-dimensional space. The quality of a space-filling curve is measured by its ability to preserve the locality (or relative distance) of multi-dimensional points in the mapped onedimensional space. The main idea is that any two D-dimensional points that are close by in the D-dimensional space should be also close by in the one-dimensional space.

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Section: Historical Backgroundmentioning

confidence: 99%

Section: Multimedia Disk Schedulingmentioning

confidence: 99%

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Space-Filling Curves

Kang¹

2016

Encyclopedia of GIS

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“…The objective of these works has been to examine the relationship between real-time requirements of individual playbacks and file system level data retrieval scheduling [5,15,19,22]. A number of works proposed disk striping techniques to efficiently support scalable streaming.…”

Section: Related Workmentioning

confidence: 99%

Storage technique for real-time streaming of layered video

2008

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Scalable streaming technology has been proposed to effectively support heterogeneous devices with dynamically varying bandwidth. From the file system's point of view, scalable streaming introduces another dimension of complexity in disk scheduling. Most of the existing efforts on multimedia file systems are dedicated to I /O scheduling algorithm and data placement scheme that efficiently guarantee I /O bandwidth. The important underlying assumption in these efforts is that most of the multimedia file accesses are simple playback operations and therefore are sequential. However, this workload characteristic is not valid in scalable streaming environment. In a scalable streaming environment, i.e., when only a subset of imagery is retrieved, the playback does not necessarily coincide with the sequential access on the file. The current file structure and the file system organization leaves much to be desired for supporting scalable streaming service. In this work, we propose a file system scheme, Harmonic Placement to efficiently support Communicated by P. Shenoy. scalable streaming. The basic idea of Harmonic placement is to cluster the frequently accessed layers together to avoid unnecessary disk seeks. The data blocks are partitioned into two sets with respect to the layers: lower layers and upper layers. In Harmonic placement, the data blocks in the lower layers are placed with respect to their frame sequence and the data blocks in the upper layers are clustered according to the layers they belong to. We develop elaborate performance models for three different file system schemes: Progressive placement, Interleaved Placement and Harmonic Placement. We investigate the performance of the file server with different file system schemes. It was found that file system performance is very sensitive to the file organization scheme. When most of the service requests are for low-quality video (e.g., 128 Kbits/s ISDN), Progressive placement scheme supports twice as many sessions as the Interleaved placement scheme. When most of the service requests are for high-quality video (e.g., 1.5 Mbits/s MPEG-2 DVD quality), Interleaved placement can support twice as many requests as Progressive placement. In both cases, Harmonic placement scheme yields the most promising performance.

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“…Space-filling curves (SFCs) have been extensively used as a mapping scheme from the discrete multi-dimensional space into the one-dimensional space (e.g., see [6,9,11,15,18,24,28,30,36,44]). A space-filling curve is a thread that goes through all the points in the discrete space while visiting each point only one time.…”

Section: Introductionmentioning

confidence: 99%

Irregularity in high-dimensional space-filling curves

Mokbel

Aref

2010

Distrib Parallel Databases

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A space-filling curve is a way of mapping the discrete multi-dimensional space into the one-dimensional space. It acts like a thread that passes through every cell element (or pixel) in the discrete multi-dimensional space so that every cell is visited exactly once. Thus, a space-filling curve imposes a linear order of the cells in the multi-dimensional space. There are numerous kinds of space-filling curves. The difference between such curves is in their way of mapping to the one-dimensional space. Selecting the appropriate curve for any application requires knowledge of the mapping scheme provided by each space-filling curve. Irregularity is proposed as a quantitative measure for the ordering quality imposed by space-filling curve mapping. The lower the irregularity the better the space-filling curve in preserving the order of the discrete multi-dimensional space. Five space-filling curves (the Sweep, Scan, Peano, Gray, and Hilbert) are analyzed with respect to irregularity. Closed formulas are developed to compute the irregularity in any dimension k for a D-dimensional space-filling curve with grid size N. A comparative study of different space-filling curves with respect to the irregularity is conducted and results are presented and discussed. We find out that for an application that is biased toward one of the dimensions, the Sweep or the Scan space-filling curves are the best choice. For high-dimensional applications, the Peano space-filling curve would be the best choice. For applications that require fairness among various dimensions, the Hilbert and Gray space-filling curves are the best choice. Communicated by Hosagrahar Jagadish.

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Scalable multimedia disk scheduling

Abstract: Abstract

Cited by 12 publications

References 23 publications

Space-Filling Curves

Space-Filling Curves

Storage technique for real-time streaming of layered video

Irregularity in high-dimensional space-filling curves

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