Quality-Aware Replication of Multimedia Data

In contrast to alpha-numerical data, multimedia data can have a wide range of quality parameters such as spatial and temporal resolution, and compression format. Users can request data with a specific quality requirement due to the needs of their applications, or the limitations of their resources....

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Published in:Database and Expert Systems Applications pp. 240 - 249
Main Authors: Tu, Yi-Cheng, Yan, Jingfeng, Prabhakar, Sunil
Format: Book Chapter Conference Proceeding
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
Series:Lecture Notes in Computer Science
Subjects:
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Dynamic Replication
Exact sciences and technology
Greedy Algorithm
Information systems. Data bases
Media Object
Memory organisation. Data processing
Multimedia Data
Query Rate
Software
Multimedia
Database query
Optimal algorithm
Video signal
Transcoding
Modeling
Replica
Optimization
Data conversion
Algorithm performance
Numerical data
Optimal solution
Heuristic method
NP hard problem
Greedy algorithm
Database
Replication
Artificial intelligence
Spatial resolution
User behavior
Mathematical programming
ISBN:3540285660, 9783540285663
ISSN:0302-9743, 1611-3349
Online Access:Get full text
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Abstract In contrast to alpha-numerical data, multimedia data can have a wide range of quality parameters such as spatial and temporal resolution, and compression format. Users can request data with a specific quality requirement due to the needs of their applications, or the limitations of their resources. On-the-fly conversion of multimedia data (such as video transcoding) is very CPU intensive and can limit the level of concurrent access supported by the database. Storing all possible replicas, on the other hand, requires unacceptable increases in storage requirements. Although replication has been well studied, to the best of our knowledge, the problem of multiple-quality replication has not been addressed. In this paper we address the problem of multiple-quality replica selection subject to an overall storage constraint. We establish that the problem is NP-hard and provide heuristic solutions under a soft quality system model where users are willing to negotiate their quality needs. An important optimization goal under such a model is to minimize utility loss. We propose a powerful greedy algorithm to solve this optimization problem. Extensive simulations show that our algorithm finds near-optimal solutions. The algorithm is flexible in that it can be extended to deal with replica selection for multiple media objects and changes of query pattern. We also discuss an extended version of the algorithm with potentially better performance.
AbstractList In contrast to alpha-numerical data, multimedia data can have a wide range of quality parameters such as spatial and temporal resolution, and compression format. Users can request data with a specific quality requirement due to the needs of their applications, or the limitations of their resources. On-the-fly conversion of multimedia data (such as video transcoding) is very CPU intensive and can limit the level of concurrent access supported by the database. Storing all possible replicas, on the other hand, requires unacceptable increases in storage requirements. Although replication has been well studied, to the best of our knowledge, the problem of multiple-quality replication has not been addressed. In this paper we address the problem of multiple-quality replica selection subject to an overall storage constraint. We establish that the problem is NP-hard and provide heuristic solutions under a soft quality system model where users are willing to negotiate their quality needs. An important optimization goal under such a model is to minimize utility loss. We propose a powerful greedy algorithm to solve this optimization problem. Extensive simulations show that our algorithm finds near-optimal solutions. The algorithm is flexible in that it can be extended to deal with replica selection for multiple media objects and changes of query pattern. We also discuss an extended version of the algorithm with potentially better performance.
Author Prabhakar, Sunil
Tu, Yi-Cheng
Yan, Jingfeng
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Keywords Multimedia
Database query
Optimal algorithm
Video signal
Transcoding
Modeling
Replica
Optimization
Data conversion
Algorithm performance
Numerical data
Optimal solution
Heuristic method
NP hard problem
Greedy algorithm
Database
Replication
Artificial intelligence
Spatial resolution
User behavior
Mathematical programming
Language English
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PublicationTitle Database and Expert Systems Applications
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Snippet In contrast to alpha-numerical data, multimedia data can have a wide range of quality parameters such as spatial and temporal resolution, and compression...
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SubjectTerms Applied sciences
Artificial intelligence
Computer science; control theory; systems
Dynamic Replication
Exact sciences and technology
Greedy Algorithm
Information systems. Data bases
Media Object
Memory organisation. Data processing
Multimedia Data
Query Rate
Software
Title Quality-Aware Replication of Multimedia Data
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