A Review of Horizontal Fragmentation Methods Considering Multimedia Data and Dynamic Access Patterns

2003 ◽

Vol 03 (01) ◽

pp. 95-117 ◽

Cited By ~ 1

Author(s):

SUNIL PRABHAKAR ◽

RAHUL CHARI

Keyword(s):

Large Scale ◽

Data Access ◽

Multimedia Data ◽

Secondary Storage ◽

Storage And Retrieval ◽

Multiple User ◽

Large Size ◽

Tertiary Storage ◽

Hierarchical Storage ◽

Access Patterns

Multimedia data poses challenges for efficient storage and retrieval due to its large size and playback timing requirements. For applications that store very large volumes of multimedia data, hierarchical storage offers a scalable and economical alternative to store data on magnetic disks. In a hierarchical storage architecture data is stored on a tape or optical disk based tertiary storage layer with the secondary storage disks serving as a cache or buffer. Due to the need for swapping media on drives, retrieving multimedia data from tertiary storage can potentially result in large delays before playback (startup latency) begins as well as during playback (jitter). In this paper we address the important problem of reducing startup latency and jitter for very large multimedia repositories. We propose that secondary storage should not be used as a cache in the traditional manner — instead, most of the secondary storage should be used to permanently store partial objects. Furthermore, replication is employed at the tertiary storage level to avoid expensive media switching. In particular, we show that by saving the initial segments of documents permanently on secondary storage, and replicating them on tertiary storage, startup latency can be significantly reduced. Since we are effectively reducing the amount of secondary storage available for buffering the data from tertiary storage, an increase in jitter may be expected. However, our results show that the technique also reduces jitter, in contrast to the expected behavior. Our technique exploits the pattern of data access. Advance knowledge of the access pattern is helpful, but not essential. Lack of this information or changes in access patterns are handled through adaptive techniques. Our study addresses both single- and multiple-user scenarios. Our results show that startup latency can be reduced by as much as 75% and jitter practically eliminated through the use of these techniques.

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Road vehicles � Multimedia data exchange format for impact tests

10.3403/30290173u ◽

2019 ◽

Keyword(s):

Data Exchange ◽

Multimedia Data ◽

Road Vehicles ◽

Data Exchange Format ◽

Impact Tests ◽

Exchange Format

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Road vehicles. Multimedia data exchange format for impact tests

10.3403/30290173 ◽

2014 ◽

Keyword(s):

Data Exchange ◽

Multimedia Data ◽

Road Vehicles ◽

Data Exchange Format ◽

Impact Tests ◽

Exchange Format

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Road vehicles � Multimedia data exchange format for impact tests

10.3403/30375479 ◽

2019 ◽

Keyword(s):

Data Exchange ◽

Multimedia Data ◽

Road Vehicles ◽

Data Exchange Format ◽

Impact Tests ◽

Exchange Format

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Evaluation of access patterns from log Ontology with DL-safe rules

Journal of Computer Applications ◽

10.3724/sp.j.1087.2009.01401 ◽

2009 ◽

Vol 29 (5) ◽

pp. 1401-1404

Author(s):

Ming SUN ◽

Bo CHEN ◽

Ming-tian ZHOU

Keyword(s):

Access Patterns

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An Efficient Shot Boundary Detection Using Data-cube Searching Technique

Recent Advances in Computer Science and Communications ◽

10.2174/2213275912666190830141628 ◽

2020 ◽

Vol 13 (4) ◽

pp. 798-807

Author(s):

J. Kavitha ◽

P. Arockia Jansi Rani ◽

P. Mohamed Fathimal ◽

Asha Paul

Keyword(s):

Texture Features ◽

Boundary Detection ◽

Data Cube ◽

Multimedia Data ◽

Shot Boundary Detection ◽

Gradual Transition ◽

Detection Rates ◽

Effective Manner ◽

Shot Boundary ◽

Shot Transitions

Background:: In the internet era, there is a prime need to access and manage the huge volume of multimedia data in an effective manner. Shot is a sequence of frames captured by a single camera in an uninterrupted space and time. Shot detection is suitable for various applications such that video browsing, video indexing, content based video retrieval and video summarization. Objective:: To detect the shot transitions in the video within a short duration. It compares the visual features of frames like correlation, histogram and texture features only in the candidate region frames instead of comparing the full frames in the video file. Methods: This paper analyses candidate frames by searching the values of frame features which matches with the abrupt detector followed by the correct cut transition frame with in the datacube recursively until it detects the correct transition frame. If they are matched with the gradual detector, then it will give the gradual transition ranges, otherwise the algorithm will compare the frames within the next datacube to detect shot transition. Results:: The total average detection rates of all transitions computed in the proposed Data-cube Search Based Shot Boundary Detection technique are 92.06 for precision, 96.92 for recall and 93.94 for f1 measure and the maximum accurate detection rate. Conclusion:: Proposed method for shot transitions uses correlation value for searching procedure with less computation time than the existing methods which compares every single frame and uses multi features such as color, edge, motion and texture features in wavelet domain.

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Adaptive Real-Time Routing Protocol for (m,k)-Firm in Industrial Wireless Multimedia Sensor Networks

Sensors ◽

10.3390/s20061633 ◽

2020 ◽

Vol 20 (6) ◽

pp. 1633 ◽

Cited By ~ 2

Author(s):

Beom-Su Kim ◽

Sangdae Kim ◽

Kyong Hoon Kim ◽

Tae-Eung Sung ◽

Babar Shah ◽

...

Keyword(s):

Real Time ◽

Routing Protocol ◽

Traffic Management ◽

Research Area ◽

Multimedia Data ◽

Wireless Multimedia ◽

Multimedia Sensor Networks ◽

Proposed Model ◽

Event Information ◽

Firm Model

Many applications are able to obtain enriched information by employing a wireless multimedia sensor network (WMSN) in industrial environments, which consists of nodes that are capable of processing multimedia data. However, as many aspects of WMSNs still need to be refined, this remains a potential research area. An efficient application needs the ability to capture and store the latest information about an object or event, which requires real-time multimedia data to be delivered to the sink timely. Motivated to achieve this goal, we developed a new adaptive QoS routing protocol based on the (m,k)-firm model. The proposed model processes captured information by employing a multimedia stream in the (m,k)-firm format. In addition, the model includes a new adaptive real-time protocol and traffic handling scheme to transmit event information by selecting the next hop according to the flow status as well as the requirement of the (m,k)-firm model. Different from the previous approach, two level adjustment in routing protocol and traffic management are able to increase the number of successful packets within the deadline as well as path setup schemes along the previous route is able to reduce the packet loss until a new path is established. Our simulation results demonstrate that the proposed schemes are able to improve the stream dynamic success ratio and network lifetime compared to previous work by meeting the requirement of the (m,k)-firm model regardless of the amount of traffic.

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Machine Learning–enabled Scalable Performance Prediction of Scientific Codes

ACM Transactions on Modeling and Computer Simulation ◽

10.1145/3450264 ◽

2021 ◽

Vol 31 (2) ◽

pp. 1-28

Author(s):

Gopinath Chennupati ◽

Nandakishore Santhi ◽

Phill Romero ◽

Stephan Eidenbenz

Keyword(s):

Machine Learning ◽

Performance Prediction ◽

Prediction Models ◽

Radiation Transport ◽

Discrete Event ◽

Basic Block ◽

Distribution Models ◽

Scientific Application ◽

High Level ◽

Access Patterns

Hardware architectures become increasingly complex as the compute capabilities grow to exascale. We present the Analytical Memory Model with Pipelines (AMMP) of the Performance Prediction Toolkit (PPT). PPT-AMMP takes high-level source code and hardware architecture parameters as input and predicts runtime of that code on the target hardware platform, which is defined in the input parameters. PPT-AMMP transforms the code to an (architecture-independent) intermediate representation, then (i) analyzes the basic block structure of the code, (ii) processes architecture-independent virtual memory access patterns that it uses to build memory reuse distance distribution models for each basic block, and (iii) runs detailed basic-block level simulations to determine hardware pipeline usage. PPT-AMMP uses machine learning and regression techniques to build the prediction models based on small instances of the input code, then integrates into a higher-order discrete-event simulation model of PPT running on Simian PDES engine. We validate PPT-AMMP on four standard computational physics benchmarks and present a use case of hardware parameter sensitivity analysis to identify bottleneck hardware resources on different code inputs. We further extend PPT-AMMP to predict the performance of a scientific application code, namely, the radiation transport mini-app SNAP. To this end, we analyze multi-variate regression models that accurately predict the reuse profiles and the basic block counts. We validate predicted SNAP runtimes against actual measured times.

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