NSTL国家科技图书文献中心

1. WS-DOA: Design of Hybrid Heuristic Algorithm for Deriving Multi-Objective Function of Optimal Task Scheduling and VM Migration Over Cloud Sector NSTL国家科技图书文献中心

Ravi Gugulothu | Suneetha Bulla ... - 《Transactions on Emerging Telecommunications Technologies》 - 2025,36(4) - e70104～ - 共27页

摘要： planning and VM migration, which effectively address | scheduling and VM migration* through the derivation of a* | VM migration. | Machine (VM) while ensuring profitability. Various | consumption, response time, and security. Likewise, VM

关键词： Multiscale dilated recurrent neural network | Optimal task scheduling and VM migration | Water strider-based dingo optimization algorithm

2. DRAP-CPU: a novel vm migration approach through a dynamic prioritized resource allocation strategy NSTL国家科技图书文献中心

Kaur, Harmeet | Gargrish, Shubham - 《Microsystem technologies》 - 2025,31(3) - 749～760 - 共12页

摘要： Machine (VM) migration, focusing primarily on the | objective of our research is to enhance VM migration | designed to address the common challenges in VM migration | -focused strategy for VM migration. This approach not | VM migration, our study provides a comprehensive

关键词： VIRTUAL MACHINE MIGRATION | ENERGY EFFICIENCY | MANAGEMENT | ALGORITHM

3. Cost and energy aware migration through dependency analysis of VM components in virtual cloud infrastructure NSTL国家科技图书文献中心

Nirmalya Mukhopadhya... | Babul P. Tewari - 《Computing》 - 2025,107(1) - 1.1～1.44 - 共44页

摘要：. Efficient VM migration* and dynamic virtual machine* | intricate dependencies among virtual machine (VM | resources, which are used in deciding competent VM | migration strategies. This paper presents an innovative | coefficient for conducting dependency analysis of VM

关键词： 62H20 | 60E05 | 35E10

4. Enhancing Security and Performance in Live VM Migration: A Machine Learning-Driven Framework With Selective Encryption for Enhanced Security and Performance in Cloud Computing Environments NSTL国家科技图书文献中心

Raseena M. Haris | Mahmoud Barhamgi ... - 《Expert systems》 - 2025,42(2) - e13823.1～e13823.15 - 共15页

摘要：Live virtual machine (LVM) migration* is* | safeguarding sensitive data during migration, particularly in | operations. Existing migration* methods often compromise* | migration process. Our approach intelligently predicts | optimal migration* times while selectively encrypting*

关键词： cloud computing | dirty pages | live virtual machine migration | pre-copy | memory migration | security | selective encryption

5. Evaluation of time-based virtual machine migration as moving target defense against host-based attacks NSTL国家科技图书文献中心

Matheus Torquato | Paulo Maciel ... - 《The Journal of Systems and Software》 - 2025,219(Jan.) - 112222.1～112222.16 - 共16页

摘要： Machine (VM) migration* could be used as MTD against* | how to select a proper VM migration-based MTD | defense in a VM migration-enabled setup. First, we | existing physical hosts. This way, when the attacker's VM | Moving Target Defense (MTD) consists of

关键词： PyMTDEvaluator | Moving target defense | Petri nets | VM migration | Dynamic platform technique

6. An energy-aware migration framework using metaheuristic algorithm in cloud computing NSTL国家科技图书文献中心

Singhal, Saurabh | Sharma, Ashish - 《Knowledge and information systems》 - 2025,67(2) - 1373～1398 - 共26页

摘要： metaheuristic Rock Hyrax algorithm-based cloud VM migration | nodes. A multi-objective VM migration* function* | gray wolf optimization. The migration* technique* | Pervasive computing requires dynamic, energy | -efficient cloud architecture to deploy services in VMs to

关键词： Cloud computing | Energy consumption | Makespan time | Resource utilization | Rock Hyrax optimization | SLA violations | VM migration

7. A reinforcement learning‑based GWO‑RNN approach for energy efficiency in data centers by minimizing virtual machine migration NSTL国家科技图书文献中心

Parsa Parsafar - 《The Journal of Supercomputing》 - 2025,81(1) - 184.1～184.38 - 共38页

摘要： the context of virtual machine (VM) migrations | unnecessary VM migrations. The use of GWO optimizes the RNNs | energyefficient VM management in cloud environments, offering a | In the era of exponential data growth, data | centers face a pressing need to manage energy

关键词： Data center | Energy efficiency | Recurrent neural networks (RNNs) | Virtual machine (VM) migration | Gray wolf optimizer (GWO) | Reinforcement learning (RL)

8. AGOA: Adam gazelle optimisation algorithm for collaborative e-learning application in cloud computing with load balancing NSTL国家科技图书文献中心

N. Venkatesh Naik | K. Madhavi - 《International journal of wireless and mobile computing》 - 2025,28(1) - 20～33 - 共14页

摘要： to user access, a Virtual Machine (VM) migration | greater than the threshold, VM migration* is conducted* | the VM in a round-robin manner and predict the load | . The objectives considered for this migration* are CPU* | utilisation, energy consumption, makespan and migration* cost*

关键词： collaborative e-learning | cloud computing | load balancing | Adam optimisation | Adam | GOA | gazelle optimisation algorithm

9. A Modified Bat Mechanism for Virtual Machine Migration in a Cloud Environment NSTL国家科技图书文献中心

Archana | Narander Kumar - 《SN Computer Science》 - 2025,6(1) - 74～ - 共13页

摘要： is to carry out the VM migration* as effectively as* | possible by shortening the migration* process, lowering* | addresses the aforementioned problems and completes the VM | migration effectively. The fitness function calculation | (physical machines) and complete migration* promptly rather*

关键词： Modified bat algorithm | Virtual machine migration | Cloud environment | Meta-heuristic algorithm | Makespan | Migration time

10. Rethinking Cost-Efficient VM Scheduling on Public Edge Platforms: A Service Provider’s Perspective NSTL国家科技图书文献中心

Yanan Li | Xiao Ma ... - 《IEEE transactions on mobile computing》 - 2025,24(3) - 1846～1858 - 共13页

摘要： bandit-based VM migration* and seasonality-aware VM* | reveals limitations of the status quo VM scheduling | . However, resolving VM scheduling considering static | Prior studies on traditional centralized | clouds independently optimizing static resource

关键词： Costs | Throughput | Bandwidth | Resource management | Job shop scheduling | Dynamic scheduling | Quality of experience | Mobile computing | Hardware | Wide area networks

摘要： planning and VM migration, which effectively address | scheduling and VM migration through the derivation of a | VM migration. | Machine (VM) while ensuring profitability. Various | consumption, response time, and security. Likewise, VM

关键词： Multiscale dilated recurrent neural network | Optimal task scheduling and VM migration | Water strider-based dingo optimization algorithm

摘要： Machine (VM) migration, focusing primarily on the | objective of our research is to enhance VM migration | designed to address the common challenges in VM migration | -focused strategy for VM migration. This approach not | VM migration, our study provides a comprehensive

关键词： VIRTUAL MACHINE MIGRATION | ENERGY EFFICIENCY | MANAGEMENT | ALGORITHM

摘要：. Efficient VM migration and dynamic virtual machine | intricate dependencies among virtual machine (VM | resources, which are used in deciding competent VM | migration strategies. This paper presents an innovative | coefficient for conducting dependency analysis of VM

关键词： 62H20 | 60E05 | 35E10

摘要：Live virtual machine (LVM) migration is | safeguarding sensitive data during migration, particularly in | operations. Existing migration methods often compromise | migration process. Our approach intelligently predicts | optimal migration times while selectively encrypting

关键词： cloud computing | dirty pages | live virtual machine migration | pre-copy | memory migration | security | selective encryption

摘要： Machine (VM) migration could be used as MTD against | how to select a proper VM migration-based MTD | defense in a VM migration-enabled setup. First, we | existing physical hosts. This way, when the attacker's VM | Moving Target Defense (MTD) consists of

关键词： PyMTDEvaluator | Moving target defense | Petri nets | VM migration | Dynamic platform technique

摘要： metaheuristic Rock Hyrax algorithm-based cloud VM migration | nodes. A multi-objective VM migration function | gray wolf optimization. The migration technique | Pervasive computing requires dynamic, energy | -efficient cloud architecture to deploy services in VMs to

关键词： Cloud computing | Energy consumption | Makespan time | Resource utilization | Rock Hyrax optimization | SLA violations | VM migration

摘要： the context of virtual machine (VM) migrations | unnecessary VM migrations. The use of GWO optimizes the RNNs | energyefficient VM management in cloud environments, offering a | In the era of exponential data growth, data | centers face a pressing need to manage energy

关键词： Data center | Energy efficiency | Recurrent neural networks (RNNs) | Virtual machine (VM) migration | Gray wolf optimizer (GWO) | Reinforcement learning (RL)

摘要： to user access, a Virtual Machine (VM) migration | greater than the threshold, VM migration is conducted | the VM in a round-robin manner and predict the load | . The objectives considered for this migration are CPU | utilisation, energy consumption, makespan and migration cost

关键词： collaborative e-learning | cloud computing | load balancing | Adam optimisation | Adam | GOA | gazelle optimisation algorithm

摘要： is to carry out the VM migration as effectively as | possible by shortening the migration process, lowering | addresses the aforementioned problems and completes the VM | migration effectively. The fitness function calculation | (physical machines) and complete migration promptly rather

关键词： Modified bat algorithm | Virtual machine migration | Cloud environment | Meta-heuristic algorithm | Makespan | Migration time

摘要： bandit-based VM migration and seasonality-aware VM | reveals limitations of the status quo VM scheduling | . However, resolving VM scheduling considering static | Prior studies on traditional centralized | clouds independently optimizing static resource

关键词： Costs | Throughput | Bandwidth | Resource management | Job shop scheduling | Dynamic scheduling | Quality of experience | Mobile computing | Hardware | Wide area networks

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国家科技图书文献中心

摘要： planning and VM migration, which effectively address | scheduling and VM migration* through the derivation of a* | VM migration. | Machine (VM) while ensuring profitability. Various | consumption, response time, and security. Likewise, VM

摘要：. Efficient VM migration* and dynamic virtual machine* | intricate dependencies among virtual machine (VM | resources, which are used in deciding competent VM | migration strategies. This paper presents an innovative | coefficient for conducting dependency analysis of VM

摘要：Live virtual machine (LVM) migration* is* | safeguarding sensitive data during migration, particularly in | operations. Existing migration* methods often compromise* | migration process. Our approach intelligently predicts | optimal migration* times while selectively encrypting*

摘要： Machine (VM) migration* could be used as MTD against* | how to select a proper VM migration-based MTD | defense in a VM migration-enabled setup. First, we | existing physical hosts. This way, when the attacker's VM | Moving Target Defense (MTD) consists of

摘要： metaheuristic Rock Hyrax algorithm-based cloud VM migration | nodes. A multi-objective VM migration* function* | gray wolf optimization. The migration* technique* | Pervasive computing requires dynamic, energy | -efficient cloud architecture to deploy services in VMs to

摘要： to user access, a Virtual Machine (VM) migration | greater than the threshold, VM migration* is conducted* | the VM in a round-robin manner and predict the load | . The objectives considered for this migration* are CPU* | utilisation, energy consumption, makespan and migration* cost*

摘要： bandit-based VM migration* and seasonality-aware VM* | reveals limitations of the status quo VM scheduling | . However, resolving VM scheduling considering static | Prior studies on traditional centralized | clouds independently optimizing static resource