An In-Depth Analysis of VM Allocation and Load Balancing Parallel Strategies in Cloud Computing: A Systematic Review
Keywords:
Cloud Data Centre; Cloud Computing; Energy Consumption; VirtualizationAbstract
The adoption of innovative technology, particularly cloud computing, has attracted users and information technology companies due to its numerous advantages, such as cost savings, remote work capabilities, automatic syncing, data backups, and easy accessibility. However, the increasing demands of end users and the need to expand data centers have led to challenges for Cloud Service Providers (CSPs), including high energy consumption and operational costs, resulting in a rise in carbon dioxide emissions. To address these environmental concerns, the concept of Green Cloud Computing has emerged, aiming to create an eco-friendly computing environment. In addition, symmetrical strategies have also been employed to reduce energy consumption, operational costs, and CO2 emissions in Cloud Data Centers (CDCs) through resource allocation, virtualization, and Virtual Machine (VM) migration. Virtualization technology in cloud computing offers cost-effective deployment of virtual resources. The use of symmetrical strategies ensures energy efficiency and load balancing among Physical Machines (PMs), allowing customers to access and configure cloud resources based on a pay-per-use model. However, the presence of heterogeneous servers and dynamic resource usage within VMs in CDCs can lead to resource imbalances, resulting in performance degradation and violation of Service Level Agreements (SLAs). To achieve effective scheduling and address these issues, load balancing algorithms have been developed to support elastic scheduling, which is a complex problem to solve. This paper provides insights into energy consumption in CDCs, the relationship between VMs and PMs, CDC terminology, centralized and distributed management, and existing research in the field. Additionally, it presents load balancing algorithms aimed at mitigating resource imbalances in CDCs. In summary, the objective of this work is to provide the nuts and bolt understanding and knowledge of the potential algorithms of VM allocation and load balancing through comparatively analyzing of different approaches in the context of Green Cloud Computing and load balancing in CDCs.
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