Name
Abstract | ||
|---|---|---|
In this paper we present an automatic performance tuning solution for the optimization of a high-demand multimedia streaming service built on a dedicated private cloud architecture. The optimization focuses mainly on two aspects: energy efficiency and quality assurance of streaming services. As QoS factors we take into consideration the minimum initial waiting time and the cumulative disruption time of continuous playing at the client side. To achieve the best performance, a cloud-based architecture is proposed with on-demand dynamic allocation of resources and a multi-level data flow with caching capabilities. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.procs.2013.05.301 | 2013 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE |
Keywords | Field | DocType |
automatic performance tuning, multimedia streaming, server optimization, cloud infrastructure, benchmarking, caching | Client-side,Computer science,Efficient energy use,Quality of service,Computer network,Resource allocation,Multimedia,Performance tuning,Benchmarking,Data flow diagram,Cloud computing | Conference |
Volume | ISSN | Citations |
18 | 1877-0509 | 0 |
PageRank | References | Authors |
0.34 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gheorghe Sebestyen | 1 | 5 | 6.25 |
| Anca Hangan | 2 | 4 | 5.30 |
| Katalin Sebestyen | 3 | 0 | 0.34 |
| Roland Vachter | 4 | 0 | 0.68 |