Advances, Systems and Applications
Table 1 Evaluation of Heuristic Methods for Cloud Data Center Resource Management
From: A systematic review on effective energy utilization management strategies in cloud data centers
Author/Year | Algorithm/Method | Data set/ Workload | Tools/ Experiment Environment | Objective | Performance Metrics/Pros | Limitations |
|---|---|---|---|---|---|---|
S. Srikantaiah et al. [44], 2008 | Multi-Dimensional Bin Packing | Own data | Powermeter Xperf | CPU, Disk Utilization | Performance, Energy usage, and Resource utilization | RAM and Network usage are not considered |
A. Beloglazav et al. [45], 2010 | ST MM Bin Packing | Random data | CloudSim simulator | VM Consolidation | decreases operational expenses while maintaining required QoS, Savings on Energy | Utilization Threshold, Multiple Resources not considered |
A. Beloglazov et al. [46], 2012 | HeuristicBFD MBFD | PlanetLab | CloudSim | CPU Utilization | Energy Efficiency, QoS, Decreases CO2 footprint, Cost Saving | Limited Scalability, Slow Optimization, only Simulation |
A. Beloglazov et al. [43], 2012 | DVMC THR MBFD | PlanetLab | CloudSim | Dynamic V M Consolidation, VM Migration, IaaS env | SLAV, VM Migration, ESV metric, Decreases CO2 footprint | Complex workload, only simulation |
M. Arani et al. [47], 2018 | VMP-BFD | PlanetLab | CloudSim | VM Allocation, Learning Automata theory | Energy Consumption, SLAV, Migration Count | Required NN for better efficiency. |
H. Wang et al. [48], 2018 | SABFD HS | PlanetLab | CloudSim | VM Placement VM Migration, DVMC, Host overload detection | Energy Efficient, Suppressing SLAV, SLATAH, PDM, ESV, VM Migration, Host Shutdown | Real-world challenges, only simulation performance |
F F Moges et al. [27], 2019 | MFPED | Planet Lab Bitbrains | CloudSim | V M Placement, VM Migration | Energy Consumption, SLAV, VM Migrations Count | N/W devices and traffic effects are not considered |
S. Bhattacherjee et al. [49], 2019 | PMM-MBFD | PlanetLab Parallel Archive | CloudSim | V M Placement, Prediction based migration | Energy Consumption, Dynamic Thresholding | RAM and N/W uses are not considered, multi-objective optimization should be required |
X. Liu et al. [50], 2020 | DCMMT | PlanetLab | CloudSim | VM Migration Thrashing, Dynamic Consolidation | VM Migration, SLA Violation, Thrashing Index, SLATAH, PDM | No real-world cloud platform, required workload statistical properties |
S. Jangiti et al. [51], (2020) and | EMC2, VMNeAR-D, VMNeAR-E | dataset extracted from EnergyStar® API | Python environment | multi-resource fairness, virtual machine consolidation | Energy-efficient, VMP, time complexity, IaaS | VM swapping into smaller PMs in case of very low resource occupancy in a huge PM |
V. Garg et al. [52], 2021 | LATHR MBFD | HPG4, 100 hosts, 290 VM | Matlab | VM Migration, Overload Detection Policy | QoS, Energy Consumption, IER, No. of Migration, SLAV | Limited workload, real-world implementation |
F. Alharbi et al. [53], 2021 | Int2LBP_FFD Int2LBP_ACS | GTC data logs | Java | Resource Management | QoS, Energy Saving, Integrated approach, Scalable | Dynamic decision required, Public CDC, Runtime VMC |
T Kaur et al. [54], 2022 | PAEEVMM | Dynamic data by user | CloudSim Plus | Temperature Threshold | CPU utilization, Power Usage | Load Balancing, Multiple Resources |