| Autor: |
Jambigi, Murgesh V., Kumar, M. V. Vijay, Ashoka, D. V., R., Prabha |
| Předmět: |
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| Zdroj: |
International Journal on Information Technologies & Security; 2022, Vol. 14 Issue 1, p17-28, 12p |
| Abstrakt: |
This paper presents a heterogenous cloud computing environment for provisioning real-time (dynamic workload) services in a cloud computing environment. Moreover, this work also presents SLA Aware Energy Optimized (SAEO) Scheduling Algorithm to execute dynamic workload applications like the data intensive and scientific applications. The main aim of the SAEO is to bring good tradeoffs in minimizing computation time and energy consumption by employing Dynamic Voltage Frequency Scaling (DVFS) effectively utilizing system resource of cloud. SAEO achieves much better performance than existing DVFS-based scheduling in terms of computation time and energy efficiency. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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