Distributed computing has risen as a well-known worldview for facilitating an assortment of online applications and services. The present business distributed computing stages utilize a semi concentrated design, where cloud resources, such as servers and storage are hosted in a few large global data centers. Virtualization in computing is a creation of virtual (not real) of something such as hardware, software, platform or an operating system or storage, or a network device. Further, Virtual Machine (VM) technology has recently emerged as an essential building block for data centers and cluster systems, mainly due to its capabilities of isolating, consolidating, and migrating workload. Migration of VM seeks to improve the manageability, performance, and fault tolerance of systems. In a virtual cloud computing environment, a set of submitted tasks from different users are scheduled on a set of Virtual Machines (VMs), and load balancing has become a critical issue for achieving energy efficiency. Thus to solve this issue and to achieve a good load balance, a new improved optimization algorithm is introduced namely Dual Conditional Moth Flame Algorithm (DC-MFA) that takes into account of proposed multi-objective functions defining the multi-constraints like CPU utilization, energy consumption, security, make span, migration cost, and resource cost. The performance of the proposed model will be analyzed by determining migration cost, energy consumption, and response time, and security analysis as well.
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The data that support the findings of this study are openly available at https://www.kaggle.com/discdiver/clouds.
- ABC + BA:
Artificial Bee Colony–Bat Algorithm
Ant Colony Optimization
Crow Search Algorithm
Cloud Service Provider
Dual Conditional Moth Flame Algorithm
Dynamic Fault Tolerant VM Migration
Improved Levy based Whale Optimization Algorithm
Moth Flame Optimization
Time Of Appearance
VM Migration Algorithm Based On Group Selection
Whale Optimization Genetic Algorithm
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Verma, G. Secure VM Migration in Cloud: Multi-Criteria Perspective with Improved Optimization Model. Wireless Pers Commun 124, 75–102 (2022). https://doi.org/10.1007/s11277-021-09319-w