Name
Abstract | ||
|---|---|---|
The problem of cloud resource optimization is examined, while the uncertainty in demand and user feedback is considered. We propose a Markov decision process model for resource assignment in cloud-based content delivery networks. Furthermore, we include a feedback-based probabilistic model for quality of experience in the resource assignment problem. We apply dynamic programming to solve this stochastic optimization problem. In order to address the challenges regarding the computational complexity of the problem, we first present an optimal solution with linear complexity for a special case of unlimited bandwidth cloud sites. Then, we propose a sub-optimal algorithm for the generic bandwidth-constrained problem with significantly reduced complexity and quasi-optimal performance. Simulation results are presented to corroborate the merits of the proposed algorithms. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ACCESS.2018.2845740 | IEEE ACCESS |
Keywords | Field | DocType |
Cloud networks,dynamic programming,Markov decision process,quality of experience | Dynamic programming,Stochastic optimization,Computer science,Stochastic process,Quality of service,Markov decision process,Quality of experience,Computational complexity theory,Cloud computing,Distributed computing | Journal |
Volume | ISSN | Citations |
6 | 2169-3536 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ali A. Haghighi | 1 | 0 | 0.68 |
| Shahram Shahbazpanahi | 2 | 1380 | 92.74 |
| Shahram Shah-Heydari | 3 | 35 | 7.62 |