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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| Vydáno v: | Database and Expert Systems Applications s. 240 - 249 |
|---|---|
| Hlavní autoři: | , , |
| Médium: | Kapitola Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2005
Springer |
| Edice: | Lecture Notes in Computer Science |
| Témata: | |
| ISBN: | 3540285660, 9783540285663 |
| ISSN: | 0302-9743, 1611-3349 |
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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. |
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| 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 |
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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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