Task consolidation based power consumption minimization in cloud computing environment

Article Computer Science, Information Systems

CTRV: resource based task consolidation approach in cloud for green computing

M. S. Mekala et al.

Summary: Dynamic resource provisioning is a main challenge in cloud computing. This paper proposes a Categorization of a Task with a Resource to assign VM (CTRV) scheduling approach, which assesses the resource requirement rate and categorizes tasks, leading to improved resource utilization efficiency and reduced energy consumption.

DISTRIBUTED AND PARALLEL DATABASES (2023)

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Article Computer Science, Hardware & Architecture

Elite learning Harris hawks optimizer for multi-objective task scheduling in cloud computing

Dina A. Amer et al.

Summary: This paper introduces a modified Harris hawks optimizer (ELHHO) for multi-objective scheduling problem, which uses elite opposition-based learning to enhance the standard HHO algorithm. Results show that the proposed ELHHO outperforms other algorithms and significantly improves the performance of conventional HHO.

JOURNAL OF SUPERCOMPUTING (2022)

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Article Computer Science, Hardware & Architecture

Energy and performance-efficient task scheduling in heterogeneous virtualized cloud computing

Mehboob Hussain et al.

Summary: The paper proposes an Energy and Performance-Efficient Task Scheduling Algorithm (EPETS) in a heterogeneous virtualized cloud to address the issue of energy consumption. By utilizing a two-stage scheduling approach, the algorithm aims to improve performance and reduce energy consumption within deadline constraints.

SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS (2021)

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Article Energy & Fuels

Usage impact on data center electricity needs: A system dynamic forecasting model

Martijn Koot et al.

Summary: This study presents a forecasting model for data center electricity needs based on understanding usage growth, concluding that efficiency gains from technological innovation cannot fully compensate for this growth. Simulations for the end of Moore's law and the growth of Industrial IoT were run, showing significant increases in electricity consumption. Sensitivity analysis revealed the vulnerability of data center electricity consumption to behavioral usage trends, highlighting the need for further research on the impact of usage on energy consumption.

APPLIED ENERGY (2021)

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Article Computer Science, Information Systems