Resource optimization in distributed real-time multimedia applications
| Autor: | Henri E. Bal, Frank J. Seinstra, Ran Yang, Dennis Roubos, Rob van der Mei |
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| Přispěvatelé: | Stochastics, Mathematics, Computer Systems, Network Institute, High Performance Distributed Computing, Probability, Networks and Algorithms |
| Rok vydání: | 2011 |
| Předmět: |
Binary search algorithm
Adaptive control SIMPLE (military communications protocol) Computer Networks and Communications Computer science Data stream mining Computation Distributed computing 020206 networking & telecommunications 02 engineering and technology Resource (project management) Transmission (telecommunications) Hardware and Architecture 0202 electrical engineering electronic engineering information engineering Media Technology Cluster (physics) 020201 artificial intelligence & image processing Software |
| Zdroj: | Yang, R, van der Mei, R D, Roubos, D, Seinstra, F J & Bal, H E 2012, ' Resource Optimization in Distributed Real-Time Multimedia Applications ', Multimedia Tools and Applications, vol. 59, no. 3, pp. 941-971 . https://doi.org/10.1007/s11042-011-0782-5 Multimedia Tools and Applications, 59(3), 941-971. Springer Netherlands Multimedia Tools and Applications, 59(3), 941-971 |
| ISSN: | 1573-7721 1380-7501 |
| Popis: | The research area of multimedia content analysis (MMCA) considers all aspects of the automated extraction of knowledge from multimedia archives and data streams. To adhere to strict time constraints, large-scalemultimedia applications typically are being executed on distributed systems consisting of large collections of compute clusters. In a distributed scenario, it is first essential to determine the optimal number of compute nodes used by each cluster, properly balancing the complex tradeoff between computation and communication. This issue is referred as the "resource utilization" (RU) problem. Next, it is important to tune the transmission of newly generated data sent to each cluster, so as to obtain the highest service utilization, while minimizing the need for buffering. This latter issue is referred as the problem of "just-in-time" (JIT) communication. In this paper, we first present a simple and easy-to-implement method for the RU problem, which is based on the classical binary search method. Second, we address the JIT problem by introducing a smart adaptive control method that properly reacts to the continuously changing circumstances in distributed systems. Extensive experimental validation of the two approaches on a real distributed system shows that our optimization approaches are indeed highly effective. © The Author(s) 2011. |
| Databáze: | OpenAIRE |
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