Virtual Machines Projects for ME, MTech, Masters, MS abroad, and PhD students. These Virtual Machines ieee projects are implemented with future work and extension for final year students with research paper writing and publishing. These research projects guide final year students to learn, practice, and complete their academic submissions successfully. Each project includes complete source code, project report, PPT, a tutorial, documentation, and a research paper.
Latest Virtual Machines Projects
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An Efficient Task Scheduling for Cloud Computing Platforms Using Energy Management Algorithm: A Comparative Analysis of Workflow Execution Time
This project studies how to efficiently manage tasks in cloud computing. It compares different scheduling methods to see which completes tasks faster and uses less energy. Experiments show that using more virtual machines improves performance. The Energy Management Algorithm performs the best and can save time and energy compared to other methods. -
CFWS: DRL-based Framework for Energy Cost and Carbon Footprint Optimization in Cloud Data Centers
This project focuses on making cloud data centers more energy-efficient and environmentally friendly. It uses artificial intelligence to decide when and where to move virtual machines across data centers. This helps reduce electricity use and carbon emissions while keeping services running smoothly. The system also minimizes unnecessary machine movements, saving time and energy. -
Energy Efficient Load Balancing Algorithm for Cloud Computing Using Rock Hyrax Optimization
This project focuses on improving cloud computing performance by balancing workloads across servers more efficiently. It introduces a new algorithm inspired by the Rock Hyrax to avoid uneven work distribution and reduce energy use. Tests show it speeds up processing by 10%–15% and lowers energy consumption by 8%–13%. The approach helps data centers run faster and use power more efficiently. -
Event-Based Moving Target Defense in Cloud Computing with VM Migration: A Performance Modeling Approach
This project focuses on improving computer security in cloud systems. It uses a method that changes system settings, like moving virtual machines or changing IP addresses, to confuse attackers. The study models these changes to find the best ways to keep systems safe. It shows that using event-based detection works well when the system can accurately detect threats more than half the time. -
Multi Objective Prioritized Workflow Scheduling Using Deep Reinforcement Based Learning in Cloud Computing
This project focuses on efficiently scheduling tasks in cloud computing. It assigns complex workflows to the best virtual machines to reduce delays, energy use, and cost. The method uses a type of artificial intelligence called deep reinforcement learning to make these decisions dynamically. Tests showed it works better than existing scheduling methods. -
Parallel Enhanced Whale Optimization Algorithm for Independent Tasks Scheduling on Cloud Computing
This project focuses on improving how tasks are assigned in cloud computing systems. The researchers created a new algorithm that schedules tasks faster and uses resources more efficiently. It avoids common problems of existing methods, such as getting stuck on poor solutions or taking too long to run. Tests show it works better than previous algorithms, even as the number of tasks grows. -
A Hyper-Heuristic Approach for Quality of Experience Aware Service Placement Scheme in 5G Mobile Edge Computing
This project focuses on improving 5G mobile edge computing. It aims to place computing services closer to users so they get faster responses. The system predicts user movement and moves services ahead of time to improve user experience. It uses smart algorithms to balance speed, cost, and efficiency in large networks. -
A Novel Authentication Protocol for 5G gNodeBs in Service Migration Scenarios of MEC
This project focuses on making edge computing safer and faster. It ensures that services moving between network nodes are secure and verified. The researchers designed a new authentication method that follows current mobile network standards. They tested it using software tools and a real 5G network setup to confirm it works well.
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