| TITLE |
Cascading ACO-PSO Based Virtual Machine Allocation in Cloud Data Centers |
| ABSTRACT |
Cloud data centers host a large number of Virtual Machines (VMs) that continuously demand computing resources such as CPU, memory, storage, and network bandwidth. Efficient VM allocation plays a vital role in achieving high resource utilization and reducing operational energy consumption. Traditional heuristic-based allocation techniques often fail to adapt to dynamic workloads, resulting in issues such as host overloading, increased power usage, and Service Level Agreement (SLA) violations.
This project proposes a Cascading Ant Colony Optimization-Particle Swarm Optimization (ACO-PSO) approach for VM allocation in cloud computing environments. The method integrates the combinatorial search capability of ACO with the parameter tuning efficiency of PSO. ACO generates candidate VM to host mappings, while PSO optimizes parameters such as pheromone influence, heuristic weights, and utilization thresholds. An Advanced Fitness Calculator evaluates each allocation based on four key objectives: power consumption, load imbalance, network traffic, and link utilization.
The proposed Cascading method is implemented using CloudSim Plus and evaluated across multiple host configurations. Experimental results demonstrate that the Cascading ACO-PSO approach achieves better energy efficiency, lower network overhead, and improved load distribution when compared with standalone ACO, PSO, and baseline strategies. This work highlights the effectiveness of Cascading metaheuristic optimization in real world cloud resource management.
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| AUTHOR |
Abisha Anthony Rego, Apoorva A P, Gopikashree S H, Y Kavya, Rajesh T. H
Department of Computer Science and Engineering, PES Institute of Technology and Management (PESITM) Shivamogga, Karnataka, India
Assistant Professor, Department of Computer Science and Engineering, PES Institute of Technology and Management (PESITM) Shivamogga, Karnataka, India
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| PUBLICATION DATE |
2025-12-18 22:22:10 |
| VOLUME |
13 |
| ISSUE |
4 |
| DOI |
DOI: 10.15662/IJMSERH.2025.1304018 |
| PDF |
pdf/2025/10/18_Tripass A Web-Based Platform for Tricycle Permit Automation, Driver Monitoring, and QR Passenger Information Access.pdf |
| KEYWORDS |
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