Analysis and modeling of Linux server clustering methods

Abstract

Abstract Currently, cluster servers and workstation systems are primarily utilized in high-performance applications and scientific computations. A cluster involves the use of numerous computers, typically PCs or UNIX workstations, along with a significant number of storage devices and unnecessary interconnections to create what appears to users as a single high-capacity system. Cluster computing can be employed for load balancing and achieving high availability. It serves as a relatively cost-effective form of a parallel processing machine for scientific and other applications that require parallel operations. Cluster server systems combine a group of servers to provide a common processing service for clients on the network. The functionality of the methods used in the cluster is crucial for enhancing the continuity and efficiency of operations on servers. This dissertation investigates the specific features, similarities, and differences of these methods. The purpose of this article is to analyze Linux server cluster methods, examine their characteristics, and conduct a deeper analysis of cluster topologies to gain further insights. To achieve this goal, a literature review has been conducted to analyze the discoveries made by other researchers in this field. By utilizing the information gathered from the literature review and following the steps of several operational researches, this study demonstrates that the agility proposed by the Linux Operating System is applicable not only to older devices but also to server clustering and the configuration requirements for various clustering techniques in a real production environment.