International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 11 Issue: 05 | May 2024
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p-ISSN: 2395-0072
Performance and Scalability of Cloud Object Stores: Systematic Literature Review Shyam Burkule1, Ramprasad Chinthekindi 2 ---------------------------------------------------------------------***-----------------------------------------------------------Abstract—In recent times, the adoption of cloud object stores scalability, resource allocation, and computing costs. It has been increasing fast due to their combination of important simplifies system operations and eliminates the need to benefits, including high availability, elasticity, and a pricing understand intricate details of cloud technologies, thereby model that enables applications to scale according to demand. reducing the indirect cost of studying [3]. The primary Currently, the common approach is to either utilize a single set providers of CC services are predominantly firms that of configuration settings or depend on statically pre-set storage specialize in the IT industry and provide solutions and rules for a cloud object store deployment, even when the store is services for CC. This includes infrastructure, data centers, and utilized to support various types of applications with changing various tools associated with CC platforms. Cloud vendors like requirements. The significant disparity between the specific Amazon Web Services (AWS), alongsideMicrosoft Azure, demands and capabilities of the object store’s many alongside Google Cloud Platform, alongside Red Hat, and applications is a pressing matter that needs to be resolved to VMware each possess distinct traits and product offerings [4]. attain optimal efficiency and performance. This investigation’s chief goal is to explore the performance and scalability of cloud object stores through research analysis. The study utilizes a comprehensive literature review methodology. This study examined a total of 30 papers that were published from 2018 to 2024. This research suggests that comparing the specifications and techniques of services offered by different cloud vendors can provide a more impartial assessment of the capacity and promise of cloud computing (CC) and object storage. This comparison helps eliminate bias risk and delivers a more accurate evaluation of the technology. The assessments yield significant information regarding the strengths and limitations of various cloud storage (CS) systems. This aids organizations in making educated decisions when choosing and improving their storage infrastructure to suit changing business requirements. Index Terms—Cloud Computing; Object Storage; Performance; Scalability; Cloud Storage Systems.
Fig. 1: Cloud Computing [5]
I. INTRODUCTION The proliferation of the Internet has led to the creation of numerous little files through Web applications. Internet users contribute to this by uploading massive quantities of photographs, movies, and music, while the daily exchange of emails reaches the hundreds of billions [1]. Based on statistics from the Internet Data Centre (IDC), the data will grow by 44 times in the next decade. Out of this, 80% will be unstructured data, with most of it being inactive [2]. The block storage area network (SAN) alongside network attached storage (NAS), which have petabyte-level expansion file storage potential, cannot manage such a massive volume of data. Typically, the size of a logical unit number (LUN) on a block storage area network (SAN) is limited to just a few terabytes (TB). CC effectively addresses concerns related to
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Fig. 2: Cloud Computing Vendors [6]
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