A Survey on Load Balancing Algorithms for VM Placement in Cloud Computing

TL;DR

This survey reviews various load balancing algorithms for VM placement in cloud data centers, highlighting challenges, classifications, and future research directions to improve resource utilization and performance.

Contribution

It provides a comprehensive classification and analysis of existing load balancing algorithms for VM placement in cloud computing environments.

Findings

Identifies key challenges in VM load balancing.

Classifies algorithms based on their approaches and strategies.

Highlights gaps and potential areas for future research.

Abstract

The emergence of cloud computing based on virtualization technologies brings huge opportunities to host virtual resource at low cost without the need of owning any infrastructure. Virtualization technologies enable users to acquire, configure and be charged on pay-per-use basis. However, Cloud data centers mostly comprise heterogeneous commodity servers hosting multiple virtual machines (VMs) with potential various specifications and fluctuating resource usages, which may cause imbalanced resource utilization within servers that may lead to performance degradation and service level agreements (SLAs) violations. To achieve efficient scheduling, these challenges should be addressed and solved by using load balancing strategies, which have been proved to be NP-hard problem. From multiple perspectives, this work identifies the challenges and analyzes existing algorithms for allocating VMs to PMs in infrastructure Clouds, especially focuses on load balancing. A detailed classification targeting load balancing algorithms for VM placement in cloud data centers is investigated and the surveyed algorithms are classified according to the classification. The goal of this paper is to provide a comprehensive and comparative understanding of existing literature and aid researchers by providing an insight for potential future enhancements.