Effect of Hyper-Threading in Latency-Critical Multithreaded Cloud Applications and Utilization Analysis of the Major System Resources

Pons, Lucía; Feliu, Josué; Puche, Jose; Huang, Chaoyi; Petit, Salvador; Pons, Julio; Gómez, María E.; Sahuquillo, Julio

doi:10.1016/j.future.2022.01.025

Cited by 7 publications

(2 citation statements)

References 16 publications

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“…Through the course of our research, we were able to distinguish and categorize the most prevalent types of virtualization, as depicted in Table 5 and illustrated in Figure 7. These types broadly encompass virtualization of servers, networks, storage, data, desktops, and applications (Li et al, 2022;Liu., 2021;Nazarov et al, 2020;Park et al, 2021;Pons, et al, 2022;Qazi, 2020;Radchenko et al, 2019;Rosioru et al, 2022;Saravanakumar et al, 2022). The diversity in types of virtualization underscores the broad applicability and immense potential of this technology in transforming various aspects of computing and information technology.…”

Section: Current Types Of Virtualizationmentioning

confidence: 99%

Virtualization Development Trends: Scoping Review

Aseeva,

Yukhnin,

Uvarov

et al. 2022

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Introduction: The development of virtualization tools, which rapidly unfolded in the 1990s, continues to demonstrate a dynamic trajectory. Modern solutions in this area have significantly evolved and diversified. The relevance of the stated issues in the era of Covid-19 has received an even deeper interpretation.Purpose: This review analyzes articles on virtualization published during the pandemic years with the aim of identifying virtualization development trends.Materials and Methods: We conducted a keyword search in the Scopus database. The focus was on articles published in English from December 2019 to December 2022. The authors followed an expanded PRISMA-ScR protocol. The search identified 164 articles, of which 131, based on their title and abstract, were marked as relevant.Results: The selected articles were classified by year of publication, type of publication, country of publication, area of virtualization, mention of Covid-19, and type of virtualization. The articles included in our review indicate that virtualization had already been integrated into all spheres of life before Covid-19. However, the pandemic caused a surge, which accelerated its implementation in various areas, ranging from education and medicine to smart cities and computer technologies.Conclusion: The presented review of the subject area allowed us to identify sectors of public life that significantly influenced virtualization during the Covid19 years, as well as the most actively developing forms of virtualization, in particular, those that allow segregating computational processes and resources. It was recorded that modern solutions in the field of virtualization have significantly diversified compared to previous years and can be classified into separate categories.

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Section: Current Types Of Virtualizationmentioning

confidence: 99%

Virtualization Development Trends: Scoping Review

Aseeva,

Yukhnin,

Uvarov

et al. 2022

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“…This paper introduces Stratus, an experimental framework that overcomes all three aforementioned shortcomings and currently serves as a valuable resource for conducting resource management research within realistic environments, such as those found in cloud computing scenarios [14,15]. Stratus is based on a hardware infrastructure implementing three main node types: a server node hosting tenant applications, a client node generating requests to the server, and a storage node providing remote storage capabilities to the server.…”

Section: Introductionmentioning

confidence: 99%

A Modular Approach to Design an Experimental Framework for Resource Management Research

Pons,

Petit,

Pons

et al. 2023

Preprint

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Research on resource management focuses on optimizing system performance and energy efficiency by distributing shared resources like processor cores, caches, and main memory among competing applications. This research spans a wide range of applications, including those from high-performance computing, machine learning, and mobile computing. Existing research frameworks often simplify research by concentrating on specific characteristics, such as the architecture of the computing nodes, resource monitoring, and representative workloads. For instance, this is typically the case with cloud systems, which introduce additional complexity regarding hardware and software requirements. To avoid this complexity during research, experimental frameworks are being developed. Nevertheless, proposed frameworks often fail regarding the types of nodes included, virtualization support, and management of critical shared resources. This paper presents Stratus, an experimental framework that overcomes these limitations. Stratus includes different types of nodes, a comprehensive virtualization stack, and the ability to partition the major shared resources of the system. Even though Stratus was originally conceived to perform cloud research, its modular design allows Stratus to be extended, broadening its research use on different computing domains and platforms, matching the complexity of nowadays cloud environments.

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