DV-DVFS: merging data variety and DVFS technique to manage the energy consumption of big data processing
Abstract Data variety is one of the most important features of Big Data. Data variety is the result of aggregating data from multiple sources and uneven distribution of data. This feature of Big Data causes high variation in the consumption of processing resources such as CPU consumption. This issue...
Main Authors: | Hossein Ahmadvand, Fouzhan Foroutan, Mahmood Fathy |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2021-03-01
|
Series: | Journal of Big Data |
Subjects: | |
Online Access: | https://doi.org/10.1186/s40537-021-00437-7 |
Similar Items
-
Energy-Aware Virtual Machine Allocation in DVFS-Enabled Cloud Data Centers
by: Javad Masoudi, et al.
Published: (2022-01-01) -
CPU-GPU-Memory DVFS for Power-Efficient MPSoC in Mobile Cyber Physical Systems
by: Somdip Dey, et al.
Published: (2022-03-01) -
Energy-Efficient Intra-Task DVFS Scheduling Using Linear Programming Formulation
by: Yang Qin, et al.
Published: (2019-01-01) -
Software and DVFS Tuning for Performance and Energy-Efficiency on Intel KNL Processors
by: Enrico Calore, et al.
Published: (2018-06-01) -
Gapprox: using Gallup approach for approximation in Big Data processing
by: Hossein Ahmadvand, et al.
Published: (2019-02-01)