Advances, Systems and Applications
Table 3 Evaluation of Meta-Heuristic Algorithms 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 |
|---|---|---|---|---|---|---|
G. Kousiouris et al. [55], 2011 | GA, ANN, LR | 6 Matlab Benchmark tests | MatlabR2007b | VM performance, VM Analysis | Scheduling decisions, co-placement of VMs | No real-world application, 5% margin of error, premature convergence. |
A. Aryania et al. [56], 2018 | EVMC- ACS | Random Workload | Java | V M Consolidation, VM Migration | SLAV, Energy Consumption, migrations, sleeping PMs | No real workload, EC during VM migration not considered. |
Goyal et al. [57], 2019 | PSO and CSA | Cloudlets jobs | CloudSim | Resource migration, Utilization | Energy Consumption, Response time, and Execution time | Not for Hybrid Energy efficient model, SLAV not addressed. |
M. Tarahomi et al. [58], 2020 | Micro-GA | PlanetLab | CloudSim | V M Placement | Power Consumption, SLAV, VM migration, host shutdown | Only simulation, need real data center environment, required OpenStack-based cloud data center. |
Dubey et al. [59], 2020 | SA | Xen server | CloudSim | V M Placement, Resource Utilization | Power Consumption, Makespan, Mapping VM to PM | Static approach, Dynamic VM problem, Actual load during run time not considered |
V. Barthwal et al. [60], 2021 | AntPu ACO MH. | PlanetLab | CloudSim | V M Placement, multi-objective optimization | Energy Consumption, SLA Violations, PM Overloading, VM migration | Memory, disk, and B/W usage were not considered to predict the PMs utilization more accurately. |
S M Mirmohseni et al. [61], 2021 | PSGO LBPSGORA | Own data | Matlab, CloudSim | Load Balancing, | Cost, Energy Consumption, Resource management | Complex, real environment. |
F. Alharbi et al. [53], 2021 | Int2LBP_FFDInt2LBP_ACS | GTC data logs | Java | Resource Management | QoS, Energy Saving | Only static decision, Public CDC, Runtime VMC |
Salami et al. [62], 2021 | CSA | Benchmark datasets | MatlabR2018b | VM Placement, new cost, and perturbation functions are introduced | Power Consumption, Execution time, cost/fitness computation, servers required for VMP | Disk and bandwidth usage not considered, required VM placement with more resources, hybridizing new CS with other metaheuristics |
M H Sayadnavard et al. [63] (2022) | MOABC-VMC | PlanetLab | CloudSim | DVMC, Prediction model, VMP | SLATAH, PDM, SLAV, EC, VM migrations, ESV. | Resource overcommitment and B/W resource constraints, static cloud environment |
S. Malik et al. [64], 2022 | GA, PSO | Google cluster traces | Simulation | Multi Resource utilization | Prediction of Resources, Accuracy, Resource Utilization | Predicting disk utilization, cost-effectiveness, and network, Multi-variate resource utilization datasets |