An online video placement policy based on bandwidth to space ratio (BSR)
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
An adaptive data replication algorithm
ACM Transactions on Database Systems (TODS)
Efficient video file allocation schemes for video-on-demand services
Multimedia Systems
On balancing between transcoding overhead and spatial consumption in content adaptation
Proceedings of the 8th annual international conference on Mobile computing and networking
Multimedia Tools and Applications
Performance Modeling of Distributed and Replicated Databases
IEEE Transactions on Knowledge and Data Engineering
A Scalable Solution to the Multi-Resource QoS Problem
RTSS '99 Proceedings of the 20th IEEE Real-Time Systems Symposium
DAVE: a system for quality driven adaptive video delivery
MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
Adapting multimedia Internet content for universal access
IEEE Transactions on Multimedia
Multiquality Data Replication in Multimedia Databases
IEEE Transactions on Knowledge and Data Engineering
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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.