Abstract
Presently, digital continuous media (CM) are well established as an integral part of many applications. In recent years, a considerable amount of research has focused on the efficient retrieval of such media. Scant attention has been paid to servers that can record such streams in real time. However, more and more devices produce direct digital output streams. Hence, the need arises to capture and store these streams with an efficient data stream recorder that can handle both recording and playback of many streams simultaneously and provide a central repository for all data.
In this report we investigate memory management in the context of large scale data stream recorders. We are especially interested in finding the minimal buffer space needed that still provides adequate resources with varying workloads. We show that computing the minimal memory is an NP-complete problem and will require further study to discover efficient heuristics.
This research has bee funded in part by NSF grants EEC-9529152 (IMSC ERC) and IIS-0082826, and an unrestricted cash gift from the Lord Eoundation
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Fu, K., Zimmermann, R. (2006). Memory Management for Large Scale Data Stream Recorders. In: Seruca, I., Cordeiro, J., Hammoudi, S., Filipe, J. (eds) Enterprise Information Systems VI. Springer, Dordrecht. https://doi.org/10.1007/1-4020-3675-2_12
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DOI: https://doi.org/10.1007/1-4020-3675-2_12
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